Automated prediction of protein function and detection of functional sites from structure.

PubMed

Pazos, Florencio; Sternberg, Michael J E

2004-10-12

Current structural genomics projects are yielding structures for proteins whose functions are unknown. Accordingly, there is a pressing requirement for computational methods for function prediction. Here we present PHUNCTIONER, an automatic method for structure-based function prediction using automatically extracted functional sites (residues associated to functions). The method relates proteins with the same function through structural alignments and extracts 3D profiles of conserved residues. Functional features to train the method are extracted from the Gene Ontology (GO) database. The method extracts these features from the entire GO hierarchy and hence is applicable across the whole range of function specificity. 3D profiles associated with 121 GO annotations were extracted. We tested the power of the method both for the prediction of function and for the extraction of functional sites. The success of function prediction by our method was compared with the standard homology-based method. In the zone of low sequence similarity (approximately 15%), our method assigns the correct GO annotation in 90% of the protein structures considered, approximately 20% higher than inheritance of function from the closest homologue.

Executive Function Processes Predict Mobility Outcomes in Older Adults

PubMed Central

Gothe, Neha P.; Fanning, Jason; Awick, Elizabeth; Chung, David; Wójcicki, Thomas R.; Olson, Erin A.; Mullen, Sean P.; Voss, Michelle; Erickson, Kirk I.; Kramer, Arthur F.; McAuley, Edward

2013-01-01

BACKGROUND: There is growing evidence suggesting an association between cognitive function and physical performance in late life. This study examined the relationship between performance on executive function measures and subsequent mobility outcomes among community dwelling older adults across a 12-month randomized controlled exercise trial. DESIGN: Randomized controlled clinical trial SETTING: Champaign-Urbana, Illinois PARTICIPANTS: Community dwelling older adults (N = 179; Mage = 66.4) INTERVENTION: A 12-month exercise trial with two arms: an aerobic exercise group and a stretching and strengthening group MEASUREMENTS: Established cognitive tests of executive function including the flanker task, task switching and a dual task paradigm, and the Wisconsin card sort test. Mobility was assessed using the timed 8-foot up and go test and times to climb up and down a flight of stairs. METHODS: Participants completed the cognitive measures at baseline and the mobility measures at baseline and after 12 months of the intervention. Multiple regression analyses were conducted to determine whether baseline executive function predicted post-intervention functional performance after controlling for age, sex, education, cardiorespiratory fitness and baseline mobility levels. RESULTS: Our analyses revealed that selective baseline executive function measures, particularly performance on the flanker task (β’s =.15 to .17) and the Wisconsin card sort test (β’s =.11 to .16) consistently predicted mobility outcomes at month 12. The estimates were in the expected direction, such that better baseline performance on the executive function measures predicted better performance on the timed mobility tests independent of the intervention group. CONCLUSION: Executive functions of inhibitory control, mental set shifting and attentional flexibility were predictive of functional mobility. Given the literature associating mobility limitations with disability, morbidity, and mortality

Minimum Performance on Clinical Tests of Physical Function to Predict Walking 6,000 Steps/Day in Knee Osteoarthritis: An Observational Study.

PubMed

Master, Hiral; Thoma, Louise M; Christiansen, Meredith B; Polakowski, Emily; Schmitt, Laura A; White, Daniel K

2018-07-01

Evidence of physical function difficulties, such as difficulty rising from a chair, may limit daily walking for people with knee osteoarthritis (OA). The purpose of this study was to identify minimum performance thresholds on clinical tests of physical function predictive to walking ≥6,000 steps/day. This benchmark is known to discriminate people with knee OA who develop functional limitation over time from those who do not. Using data from the Osteoarthritis Initiative, we quantified daily walking as average steps/day from an accelerometer (Actigraph GT1M) worn for ≥10 hours/day over 1 week. Physical function was quantified using 3 performance-based clinical tests: 5 times sit-to-stand test, walking speed (tested over 20 meters), and 400-meter walk test. To identify minimum performance thresholds for daily walking, we calculated physical function values corresponding to high specificity (80-95%) to predict walking ≥6,000 steps/day. Among 1,925 participants (mean ± SD age 65.1 ± 9.1 years, mean ± SD body mass index 28.4 ± 4.8 kg/m 2 , and 55% female) with valid accelerometer data, 54.9% walked ≥6,000 steps/day. High specificity thresholds of physical function for walking ≥6,000 steps/day ranged 11.4-14.0 seconds on the 5 times sit-to-stand test, 1.13-1.26 meters/second for walking speed, or 315-349 seconds on the 400-meter walk test. Not meeting these minimum performance thresholds on clinical tests of physical function may indicate inadequate physical ability to walk ≥6,000 steps/day for people with knee OA. Rehabilitation may be indicated to address underlying impairments limiting physical function. © 2017, American College of Rheumatology.

Systematic prediction of gene function in Arabidopsis thaliana using a probabilistic functional gene network

PubMed Central

Hwang, Sohyun; Rhee, Seung Y; Marcotte, Edward M; Lee, Insuk

2012-01-01

AraNet is a functional gene network for the reference plant Arabidopsis and has been constructed in order to identify new genes associated with plant traits. It is highly predictive for diverse biological pathways and can be used to prioritize genes for functional screens. Moreover, AraNet provides a web-based tool with which plant biologists can efficiently discover novel functions of Arabidopsis genes (http://www.functionalnet.org/aranet/). This protocol explains how to conduct network-based prediction of gene functions using AraNet and how to interpret the prediction results. Functional discovery in plant biology is facilitated by combining candidate prioritization by AraNet with focused experimental tests. PMID:21886106

Testing computational prediction of missense mutation phenotypes: Functional characterization of 204 mutations of human cystathionine beta synthase

PubMed Central

Wei, Qiong; Wang, Liqun; Wang, Qiang; Kruger, Warren D.; Dunbrack, Roland L.

2010-01-01

Predicting the phenotypes of missense mutations uncovered by large-scale sequencing projects is an important goal in computational biology. High-confidence predictions can be an aid in focusing experimental and association studies on those mutations most likely to be associated with causative relationships between mutation and disease. As an aid in developing these methods further, we have derived a set of random mutations of the enzymatic domains of human cystathionine beta synthase. This enzyme is a dimeric protein that catalyzes the condensation of serine and homocysteine to produce cystathionine. Yeast missing this enzyme cannot grow on medium lacking a source of cysteine, while transfection of functional human CBS into yeast strains missing endogenous enzyme can successfully complement for the missing gene. We used PCR mutagenesis with error-prone Taq polymerase to produce 948 colonies, and compared cell growth in the presence or absence of a cysteine source as a measure of CBS function. We were able to infer the phenotypes of 204 single-site mutants, 79 of them deleterious and 125 neutral. This set was used to test the accuracy of six publicly available prediction methods for phenotype prediction of missense mutations: SIFT, PolyPhen, PMut, SNPs3D, PhD-SNP, and nsSNPAnalyzer. The top methods are PolyPhen, SIFT, and nsSNPAnalyzer, which have similar performance. Using kernel discriminant functions, we found that the difference in position-specific scoring matrix values is more predictive than the wild-type PSSM score alone, and that the relative surface area in the biologically relevant complex is more predictive than that of the monomeric proteins. PMID:20455263

Three-dimensional computed tomographic volumetry precisely predicts the postoperative pulmonary function.

PubMed

Kobayashi, Keisuke; Saeki, Yusuke; Kitazawa, Shinsuke; Kobayashi, Naohiro; Kikuchi, Shinji; Goto, Yukinobu; Sakai, Mitsuaki; Sato, Yukio

2017-11-01

It is important to accurately predict the patient's postoperative pulmonary function. The aim of this study was to compare the accuracy of predictions of the postoperative residual pulmonary function obtained with three-dimensional computed tomographic (3D-CT) volumetry with that of predictions obtained with the conventional segment-counting method. Fifty-three patients scheduled to undergo lung cancer resection, pulmonary function tests, and computed tomography were enrolled in this study. The postoperative residual pulmonary function was predicted based on the segment-counting and 3D-CT volumetry methods. The predicted postoperative values were compared with the results of postoperative pulmonary function tests. Regarding the linear correlation coefficients between the predicted postoperative values and the measured values, those obtained using the 3D-CT volumetry method tended to be higher than those acquired using the segment-counting method. In addition, the variations between the predicted and measured values were smaller with the 3D-CT volumetry method than with the segment-counting method. These results were more obvious in COPD patients than in non-COPD patients. Our findings suggested that the 3D-CT volumetry was able to predict the residual pulmonary function more accurately than the segment-counting method, especially in patients with COPD. This method might lead to the selection of appropriate candidates for surgery among patients with a marginal pulmonary function.

Multitrophic functional diversity predicts ecosystem functioning in experimental assemblages of estuarine consumers.

PubMed

Lefcheck, Jonathan S; Duffy, J Emmett

2015-11-01

The use of functional traits to explain how biodiversity affects ecosystem functioning has attracted intense interest, yet few studies have a priori altered functional diversity, especially in multitrophic communities. Here, we manipulated multivariate functional diversity of estuarine grazers and predators within multiple levels of species richness to test how species richness and functional diversity predicted ecosystem functioning in a multitrophic food web. Community functional diversity was a better predictor than species richness for the majority of ecosystem properties, based on generalized linear mixed-effects models. Combining inferences from eight traits into a single multivariate index increased prediction accuracy of these models relative to any individual trait. Structural equation modeling revealed that functional diversity of both grazers and predators was important in driving final biomass within trophic levels, with stronger effects observed for predators. We also show that different species drove different ecosystem responses, with evidence for both sampling effects and complementarity. Our study extends experimental investigations of functional trait diversity to a multilevel food web, and demonstrates that functional diversity can be more accurate and effective than species richness in predicting community biomass in a food web context.

Flight-Test Evaluation of Flutter-Prediction Methods

NASA Technical Reports Server (NTRS)

Lind, RIck; Brenner, Marty

2003-01-01

The flight-test community routinely spends considerable time and money to determine a range of flight conditions, called a flight envelope, within which an aircraft is safe to fly. The cost of determining a flight envelope could be greatly reduced if there were a method of safely and accurately predicting the speed associated with the onset of an instability called flutter. Several methods have been developed with the goal of predicting flutter speeds to improve the efficiency of flight testing. These methods include (1) data-based methods, in which one relies entirely on information obtained from the flight tests and (2) model-based approaches, in which one relies on a combination of flight data and theoretical models. The data-driven methods include one based on extrapolation of damping trends, one that involves an envelope function, one that involves the Zimmerman-Weissenburger flutter margin, and one that involves a discrete-time auto-regressive model. An example of a model-based approach is that of the flutterometer. These methods have all been shown to be theoretically valid and have been demonstrated on simple test cases; however, until now, they have not been thoroughly evaluated in flight tests. An experimental apparatus called the Aerostructures Test Wing (ATW) was developed to test these prediction methods.

Testing an earthquake prediction algorithm

USGS Publications Warehouse

Kossobokov, V.G.; Healy, J.H.; Dewey, J.W.

1997-01-01

A test to evaluate earthquake prediction algorithms is being applied to a Russian algorithm known as M8. The M8 algorithm makes intermediate term predictions for earthquakes to occur in a large circle, based on integral counts of transient seismicity in the circle. In a retroactive prediction for the period January 1, 1985 to July 1, 1991 the algorithm as configured for the forward test would have predicted eight of ten strong earthquakes in the test area. A null hypothesis, based on random assignment of predictions, predicts eight earthquakes in 2.87% of the trials. The forward test began July 1, 1991 and will run through December 31, 1997. As of July 1, 1995, the algorithm had forward predicted five out of nine earthquakes in the test area, which success ratio would have been achieved in 53% of random trials with the null hypothesis.

The Predictive Value of the Maximal Liver Function Capacity Test for the Isolation of Primary Human Hepatocytes.

PubMed

Major, Rebeka D; Kluge, Martin; Jara, Maximilian; Nösser, Maximilian; Horner, Rosa; Gassner, Joseph; Struecker, Benjamin; Tang, Peter; Lippert, Steffen; Reutzel-Selke, Anja; Geisel, Dominik; Denecke, Timm; Stockmann, Martin; Pratschke, Johann; Sauer, Igor M; Raschzok, Nathanael

2018-03-01

The need for primary human hepatocytes is constantly growing for basic research, as well as for therapeutic applications. However, the isolation outcome strongly depends on the quality of liver tissue, and we are still lacking a preoperative test that allows the prediction of the hepatocyte isolation outcome. In this study, we evaluated the "maximal liver function capacity test" (LiMAx) as predictive test for the quantitative and qualitative outcome of hepatocyte isolation. This test is already used in clinical routine to measure preoperative and to predict postoperative liver function. The patient's preoperative mean LiMAx was obtained from the patient records, and preoperative computed tomography and magnetic resonance images were used to calculate the whole liver volume to adjust the mean LiMAx. The outcome parameters of the hepatocyte isolation procedures were analyzed in correlation with the adjusted mean LiMAx. Primary human hepatocytes were isolated from partial hepatectomies (n = 64). From these 64 hepatectomies we included 48 to our study and correlated their isolation outcome parameters with volume corrected LiMAx values. From a total of 11 hepatocyte isolation procedures, metabolic parameters (albumin, urea, and aspartate aminotransferase or AST) were assessed during the hepatocyte cultivation period of 5 days. The volume adjusted mean LiMAx showed a significant positive correlation with the total cell yield (p = 0.049; r = 0.242; n = 48). The correlations of volume adjusted LiMAx values with viable cell yield and cell viability did not reach statistical significance. To create a more homogenous study group regarding tumor entities, subgroup analyses were performed. A subgroup analysis of isolations from patients with colorectal metastasis revealed a significant correlation between volume adjusted mean LiMAx and total cell yield (p = 0.012; r = 0.488; n = 21) and viable cell yield (p = 0.034; r = 0.405; n = 21

Executive Functions Predict the Success of Top-Soccer Players

PubMed Central

Vestberg, Torbjörn; Gustafson, Roland; Maurex, Liselotte; Ingvar, Martin; Petrovic, Predrag

2012-01-01

While the importance of physical abilities and motor coordination is non-contested in sport, more focus has recently been turned toward cognitive processes important for different sports. However, this line of studies has often investigated sport-specific cognitive traits, while few studies have focused on general cognitive traits. We explored if measures of general executive functions can predict the success of a soccer player. The present study used standardized neuropsychological assessment tools assessing players' general executive functions including on-line multi-processing such as creativity, response inhibition, and cognitive flexibility. In a first cross-sectional part of the study we compared the results between High Division players (HD), Lower Division players (LD) and a standardized norm group. The result shows that both HD and LD players had significantly better measures of executive functions in comparison to the norm group for both men and women. Moreover, the HD players outperformed the LD players in these tests. In the second prospective part of the study, a partial correlation test showed a significant correlation between the result from the executive test and the numbers of goals and assists the players had scored two seasons later. The results from this study strongly suggest that results in cognitive function tests predict the success of ball sport players. PMID:22496850

Graph pyramids for protein function prediction.

PubMed

Sandhan, Tushar; Yoo, Youngjun; Choi, Jin; Kim, Sun

2015-01-01

Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data.

Resting-State Functional Connectivity Predicts Cognitive Impairment Related to Alzheimer's Disease.

PubMed

Lin, Qi; Rosenberg, Monica D; Yoo, Kwangsun; Hsu, Tiffany W; O'Connell, Thomas P; Chun, Marvin M

2018-01-01

Resting-state functional connectivity (rs-FC) is a promising neuromarker for cognitive decline in aging population, based on its ability to reveal functional differences associated with cognitive impairment across individuals, and because rs-fMRI may be less taxing for participants than task-based fMRI or neuropsychological tests. Here, we employ an approach that uses rs-FC to predict the Alzheimer's Disease Assessment Scale (11 items; ADAS11) scores, which measure overall cognitive functioning, in novel individuals. We applied this technique, connectome-based predictive modeling, to a heterogeneous sample of 59 subjects from the Alzheimer's Disease Neuroimaging Initiative, including normal aging, mild cognitive impairment, and AD subjects. First, we built linear regression models to predict ADAS11 scores from rs-FC measured with Pearson's r correlation. The positive network model tested with leave-one-out cross validation (LOOCV) significantly predicted individual differences in cognitive function from rs-FC. In a second analysis, we considered other functional connectivity features, accordance and discordance, which disentangle the correlation and anticorrelation components of activity timecourses between brain areas. Using partial least square regression and LOOCV, we again built models to successfully predict ADAS11 scores in novel individuals. Our study provides promising evidence that rs-FC can reveal cognitive impairment in an aging population, although more development is needed for clinical application.

Hypothesis testing and earthquake prediction.

PubMed

Jackson, D D

1996-04-30

Requirements for testing include advance specification of the conditional rate density (probability per unit time, area, and magnitude) or, alternatively, probabilities for specified intervals of time, space, and magnitude. Here I consider testing fully specified hypotheses, with no parameter adjustments or arbitrary decisions allowed during the test period. Because it may take decades to validate prediction methods, it is worthwhile to formulate testable hypotheses carefully in advance. Earthquake prediction generally implies that the probability will be temporarily higher than normal. Such a statement requires knowledge of "normal behavior"--that is, it requires a null hypothesis. Hypotheses can be tested in three ways: (i) by comparing the number of actual earth-quakes to the number predicted, (ii) by comparing the likelihood score of actual earthquakes to the predicted distribution, and (iii) by comparing the likelihood ratio to that of a null hypothesis. The first two tests are purely self-consistency tests, while the third is a direct comparison of two hypotheses. Predictions made without a statement of probability are very difficult to test, and any test must be based on the ratio of earthquakes in and out of the forecast regions.

Hypothesis testing and earthquake prediction.

PubMed Central

Jackson, D D

1996-01-01

Requirements for testing include advance specification of the conditional rate density (probability per unit time, area, and magnitude) or, alternatively, probabilities for specified intervals of time, space, and magnitude. Here I consider testing fully specified hypotheses, with no parameter adjustments or arbitrary decisions allowed during the test period. Because it may take decades to validate prediction methods, it is worthwhile to formulate testable hypotheses carefully in advance. Earthquake prediction generally implies that the probability will be temporarily higher than normal. Such a statement requires knowledge of "normal behavior"--that is, it requires a null hypothesis. Hypotheses can be tested in three ways: (i) by comparing the number of actual earth-quakes to the number predicted, (ii) by comparing the likelihood score of actual earthquakes to the predicted distribution, and (iii) by comparing the likelihood ratio to that of a null hypothesis. The first two tests are purely self-consistency tests, while the third is a direct comparison of two hypotheses. Predictions made without a statement of probability are very difficult to test, and any test must be based on the ratio of earthquakes in and out of the forecast regions. PMID:11607663

Dichotic listening tests of functional brain asymmetry predict response to fluoxetine in depressed women and men.

PubMed

Bruder, Gerard E; Stewart, Jonathan W; McGrath, Patrick J; Deliyannides, Deborah; Quitkin, Frederic M

2004-09-01

Patients having a depressive disorder vary widely in their therapeutic responsiveness to a selective serotonin reuptake inhibitor (SSRI), but there are no clinical predictors of treatment outcome. Studies using dichotic listening, electrophysiologic and neuroimaging measures suggest that pretreatment differences among depressed patients in functional brain asymmetry are related to responsiveness to antidepressants. Two new studies replicate differences in dichotic listening asymmetry between fluoxetine responders and nonresponders, and demonstrate the importance of gender in this context. Right-handed outpatients who met DSM-IV criteria for major depression, dysthymia, or depression not otherwise specified were tested on dichotic fused-words and complex tones tests before completing 12 weeks of fluoxetine treatment. Perceptual asymmetry (PA) scores were compared for 75 patients (38 women) who responded to treatment and 39 patients (14 women) who were nonresponders. Normative data were also obtained for 101 healthy adults (61 women). Patients who responded to fluoxetine differed from nonresponders and healthy adults in favoring left- over right-hemisphere processing of dichotic stimuli, and this difference was dependent on gender and test. Heightened left-hemisphere advantage for dichotic words in responders was present among women but not men, whereas reduced right-hemisphere advantage for dichotic tones in responders was present among men but not women. Pretreatment PA was also predictive of change in depression severity following treatment. Responder vs nonresponder differences for verbal dichotic listening in women and nonverbal dichotic listening in men are discussed in terms of differences in cognitive function, hemispheric organization, and neurotransmitter function.

Parametric Bayesian priors and better choice of negative examples improve protein function prediction.

PubMed

Youngs, Noah; Penfold-Brown, Duncan; Drew, Kevin; Shasha, Dennis; Bonneau, Richard

2013-05-01

Computational biologists have demonstrated the utility of using machine learning methods to predict protein function from an integration of multiple genome-wide data types. Yet, even the best performing function prediction algorithms rely on heuristics for important components of the algorithm, such as choosing negative examples (proteins without a given function) or determining key parameters. The improper choice of negative examples, in particular, can hamper the accuracy of protein function prediction. We present a novel approach for choosing negative examples, using a parameterizable Bayesian prior computed from all observed annotation data, which also generates priors used during function prediction. We incorporate this new method into the GeneMANIA function prediction algorithm and demonstrate improved accuracy of our algorithm over current top-performing function prediction methods on the yeast and mouse proteomes across all metrics tested. Code and Data are available at: http://bonneaulab.bio.nyu.edu/funcprop.html

Graph pyramids for protein function prediction

PubMed Central

2015-01-01

Background Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Methods Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Results Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data. PMID:26044522

Predictive value of health-related fitness tests for self-reported mobility difficulties among high-functioning elderly men and women.

PubMed

Hämäläinen, H Pauliina; Suni, Jaana H; Pasanen, Matti E; Malmberg, Jarmo J; Miilunpalo, Seppo I

2006-06-01

The functional independence of elderly populations deteriorates with age. Several tests of physical performance have been developed for screening elderly persons who are at risk of losing their functional independence. The purpose of the present study was to investigate whether several components of health-related fitness (HRF) are valid in predicting the occurrence of self-reported mobility difficulties (MD) among high-functioning older adults. Subjects were community-dwelling men and women, born 1917-1941, who participated in the assessment of HRF [6.1-m (20-ft) walk, one-leg stand, backwards walk, trunk side-bending, dynamic back extension, one-leg squat, 1-km walk] and who were free of MD in 1996 (no difficulties in walking 2- km, n=788; no difficulties in climbing stairs, n=647). Postal questionnaires were used to assess the prevalence of MD in 1996 and the occurrence of new MD in 2002. Logistic regression analysis was used as the statistical method. Both inability to perform the backwards walk and a poorer result in it were associated with risk of walking difficulties in the logistic model, with all the statistically significant single test items included. Results of 1-km walk time and one-leg squat strength test were also associated with risk, although the squat was statistically significant only in two older birth cohorts. Regarding stair-climbing difficulties, poorer results in the 1-km walk, dynamic back extension and one-leg squat tests were associated with increased risk of MD. The backwards walk, one-leg squat, dynamic back extension and 1-km walk tests were the best predictors of MD. These tests are recommended for use in screening high-functioning older people at risk of MD, as well as to target physical activity counseling to those components of HRF that are important for functional independence.

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning.

PubMed

He, Zhili; Zhang, Ping; Wu, Linwei; Rocha, Andrea M; Tu, Qichao; Shi, Zhou; Wu, Bo; Qin, Yujia; Wang, Jianjun; Yan, Qingyun; Curtis, Daniel; Ning, Daliang; Van Nostrand, Joy D; Wu, Liyou; Yang, Yunfeng; Elias, Dwayne A; Watson, David B; Adams, Michael W W; Fields, Matthew W; Alm, Eric J; Hazen, Terry C; Adams, Paul D; Arkin, Adam P; Zhou, Jizhong

2018-02-20

Contamination from anthropogenic activities has significantly impacted Earth's biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly ( P < 0.05) as uranium or nitrate increased, and their changes could be used to successfully predict uranium and nitrate contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning. IMPORTANCE Disentangling the relationships between biodiversity and ecosystem functioning is an important but poorly understood topic in ecology. Predicting ecosystem functioning on the basis of biodiversity is even more difficult, particularly with microbial biomarkers. As an exploratory effort, this study used key microbial functional genes as biomarkers to provide predictive understanding of environmental contamination and ecosystem functioning. The results indicated that the overall functional gene richness

The relationship between neuropsychological tests of visuospatial function and lobar cortical thickness.

PubMed

Zink, Davor N; Miller, Justin B; Caldwell, Jessica Z K; Bird, Christopher; Banks, Sarah J

2018-06-01

Tests of visuospatial function are often administered in comprehensive neuropsychological evaluations. These tests are generally considered assays of parietal lobe function; however, the neural correlates of these tests, using modern imaging techniques, are not well understood. In the current study we investigated the relationship between three commonly used tests of visuospatial function and lobar cortical thickness in each hemisphere. Data from 374 patients who underwent a neuropsychological evaluation and MRI scans in an outpatient dementia clinic were included in the analysis. We examined the relationships between cortical thickness, as assessed with Freesurfer, and performance on three tests: Judgment of Line Orientation (JoLO), Block Design (BD) from the Fourth edition of the Wechsler Adult Intelligence Scale, and Brief Visuospatial Memory Test-Revised Copy Trial (BVMT-R-C) in patients who showed overall average performance on these tasks. Using a series of multiple regression models, we assessed which lobe's overall cortical thickness best predicted test performance. Among the individual lobes, JoLO performance was best predicted by cortical thickness in the right temporal lobe. BD performance was best predicted by cortical thickness in the right parietal lobe, and BVMT-R-C performance was best predicted by cortical thickness in the left parietal lobe. Performance on constructional tests of visuospatial function appears to correspond best with underlying cortical thickness of the parietal lobes, while performance on visuospatial judgment tests appears to correspond best to temporal lobe thickness. Future research using voxel-wise and connectivity techniques and including more diverse samples will help further understanding of the regions and networks involved in visuospatial tests.

Predicting individual brain functional connectivity using a Bayesian hierarchical model.

PubMed

Dai, Tian; Guo, Ying

2017-02-15

Network-oriented analysis of functional magnetic resonance imaging (fMRI), especially resting-state fMRI, has revealed important association between abnormal connectivity and brain disorders such as schizophrenia, major depression and Alzheimer's disease. Imaging-based brain connectivity measures have become a useful tool for investigating the pathophysiology, progression and treatment response of psychiatric disorders and neurodegenerative diseases. Recent studies have started to explore the possibility of using functional neuroimaging to help predict disease progression and guide treatment selection for individual patients. These studies provide the impetus to develop statistical methodology that would help provide predictive information on disease progression-related or treatment-related changes in neural connectivity. To this end, we propose a prediction method based on Bayesian hierarchical model that uses individual's baseline fMRI scans, coupled with relevant subject characteristics, to predict the individual's future functional connectivity. A key advantage of the proposed method is that it can improve the accuracy of individualized prediction of connectivity by combining information from both group-level connectivity patterns that are common to subjects with similar characteristics as well as individual-level connectivity features that are particular to the specific subject. Furthermore, our method also offers statistical inference tools such as predictive intervals that help quantify the uncertainty or variability of the predicted outcomes. The proposed prediction method could be a useful approach to predict the changes in individual patient's brain connectivity with the progression of a disease. It can also be used to predict a patient's post-treatment brain connectivity after a specified treatment regimen. Another utility of the proposed method is that it can be applied to test-retest imaging data to develop a more reliable estimator for individual

Predicting functional decline and survival in amyotrophic lateral sclerosis.

PubMed

Ong, Mei-Lyn; Tan, Pei Fang; Holbrook, Joanna D

2017-01-01

Better predictors of amyotrophic lateral sclerosis disease course could enable smaller and more targeted clinical trials. Partially to address this aim, the Prize for Life foundation collected de-identified records from amyotrophic lateral sclerosis sufferers who participated in clinical trials of investigational drugs and made them available to researchers in the PRO-ACT database. In this study, time series data from PRO-ACT subjects were fitted to exponential models. Binary classes for decline in the total score of amyotrophic lateral sclerosis functional rating scale revised (ALSFRS-R) (fast/slow progression) and survival (high/low death risk) were derived. Data was segregated into training and test sets via cross validation. Learning algorithms were applied to the demographic, clinical and laboratory parameters in the training set to predict ALSFRS-R decline and the derived fast/slow progression and high/low death risk categories. The performance of predictive models was assessed by cross-validation in the test set using Receiver Operator Curves and root mean squared errors. A model created using a boosting algorithm containing the decline in four parameters (weight, alkaline phosphatase, albumin and creatine kinase) post baseline, was able to predict functional decline class (fast or slow) with fair accuracy (AUC = 0.82). However similar approaches to build a predictive model for decline class by baseline subject characteristics were not successful. In contrast, baseline values of total bilirubin, gamma glutamyltransferase, urine specific gravity and ALSFRS-R item score-climbing stairs were sufficient to predict survival class. Using combinations of small numbers of variables it was possible to predict classes of functional decline and survival across the 1-2 year timeframe available in PRO-ACT. These findings may have utility for design of future ALS clinical trials.

CAN UPPER EXTREMITY FUNCTIONAL TESTS PREDICT THE SOFTBALL THROW FOR DISTANCE: A PREDICTIVE VALIDITY INVESTIGATION

PubMed Central

Hanney, William J.; Kolber, Morey J.; Davies, George J.; Riemann, Bryan

2011-01-01

Introduction: Understanding the relationships between performance tests and sport activity is important to the rehabilitation specialist. The purpose of this study was two- fold: 1) To identify if relationships exist between tests of upper body strength and power (Single Arm Seated Shot Put, Timed Push-Up, Timed Modified Pull-Up, and The Davies Closed Kinetic Chain Upper Extremity Stability Test, and the softball throw for distance), 2) To determine which variable or group of variables best predicts the performance of a sport specific task (the softball throw for distance). Methods: One hundred eighty subjects (111 females and 69 males, aged 18-45 years) performed the 5 upper extremity tests. The Pearson product moment correlation and a stepwise regression were used to determine whether relationships existed between performance on the tests and which upper extremity test result best explained the performance on the softball throw for distance. Results: There were significant correlations (r=.33 to r=.70, p=0.001) between performance on all of the tests. The modified pull-up test was the best predictor of the performance on the softball throw for distance (r2= 48.7), explaining 48.7% of variation in performance. When weight, height, and age were added to the regression equation the r2 values increased to 64.5, 66.2, and 67.5 respectively. Conclusion: The results of this study indicate that several upper extremity tests demonstrate significant relationships with one another and with the softball throw for distance. The modified pull up test was the best predictor of performance on the softball throw for distance. PMID:21712942

Blind test of physics-based prediction of protein structures.

PubMed

Shell, M Scott; Ozkan, S Banu; Voelz, Vincent; Wu, Guohong Albert; Dill, Ken A

2009-02-01

We report here a multiprotein blind test of a computer method to predict native protein structures based solely on an all-atom physics-based force field. We use the AMBER 96 potential function with an implicit (GB/SA) model of solvation, combined with replica-exchange molecular-dynamics simulations. Coarse conformational sampling is performed using the zipping and assembly method (ZAM), an approach that is designed to mimic the putative physical routes of protein folding. ZAM was applied to the folding of six proteins, from 76 to 112 monomers in length, in CASP7, a community-wide blind test of protein structure prediction. Because these predictions have about the same level of accuracy as typical bioinformatics methods, and do not utilize information from databases of known native structures, this work opens up the possibility of predicting the structures of membrane proteins, synthetic peptides, or other foldable polymers, for which there is little prior knowledge of native structures. This approach may also be useful for predicting physical protein folding routes, non-native conformations, and other physical properties from amino acid sequences.

Blind Test of Physics-Based Prediction of Protein Structures

PubMed Central

Shell, M. Scott; Ozkan, S. Banu; Voelz, Vincent; Wu, Guohong Albert; Dill, Ken A.

2009-01-01

We report here a multiprotein blind test of a computer method to predict native protein structures based solely on an all-atom physics-based force field. We use the AMBER 96 potential function with an implicit (GB/SA) model of solvation, combined with replica-exchange molecular-dynamics simulations. Coarse conformational sampling is performed using the zipping and assembly method (ZAM), an approach that is designed to mimic the putative physical routes of protein folding. ZAM was applied to the folding of six proteins, from 76 to 112 monomers in length, in CASP7, a community-wide blind test of protein structure prediction. Because these predictions have about the same level of accuracy as typical bioinformatics methods, and do not utilize information from databases of known native structures, this work opens up the possibility of predicting the structures of membrane proteins, synthetic peptides, or other foldable polymers, for which there is little prior knowledge of native structures. This approach may also be useful for predicting physical protein folding routes, non-native conformations, and other physical properties from amino acid sequences. PMID:19186130

Protein Function Prediction: Problems and Pitfalls.

PubMed

Pearson, William R

2015-09-03

The characterization of new genomes based on their protein sets has been revolutionized by new sequencing technologies, but biologists seeking to exploit new sequence information are often frustrated by the challenges associated with accurately assigning biological functions to newly identified proteins. Here, we highlight some of the challenges in functional inference from sequence similarity. Investigators can improve the accuracy of function prediction by (1) being conservative about the evolutionary distance to a protein of known function; (2) considering the ambiguous meaning of "functional similarity," and (3) being aware of the limitations of annotations in functional databases. Protein function prediction does not offer "one-size-fits-all" solutions. Prediction strategies work better when the idiosyncrasies of function and functional annotation are better understood. Copyright © 2015 John Wiley & Sons, Inc.

Executive function predicts artificial language learning

PubMed Central

Kapa, Leah L.; Colombo, John

2017-01-01

Previous research suggests executive function (EF) advantages among bilinguals compared to monolingual peers, and these advantages are generally attributed to experience controlling two linguistic systems. However, the possibility that the relationship between bilingualism and EF might be bidirectional has not been widely considered; while experience with two languages might improve EF, better EF skills might also facilitate language learning. In the current studies, we tested whether adults’ and preschool children’s EF abilities predicted success in learning a novel artificial language. After controlling for working memory and English receptive vocabulary, adults’ artificial language performance was predicted by their inhibitory control ability (Study 1) and children’s performance was predicted by their attentional monitoring and shifting ability (Study 2). These findings provide preliminary evidence suggesting that EF processes may be employed during initial stages of language learning, particularly vocabulary acquisition, and support the possibility of a bidirectional relationship between EF and language acquisition. PMID:29129958

Predicting cognitive function from clinical measures of physical function and health status in older adults.

PubMed

Bolandzadeh, Niousha; Kording, Konrad; Salowitz, Nicole; Davis, Jennifer C; Hsu, Liang; Chan, Alison; Sharma, Devika; Blohm, Gunnar; Liu-Ambrose, Teresa

2015-01-01

Current research suggests that the neuropathology of dementia-including brain changes leading to memory impairment and cognitive decline-is evident years before the onset of this disease. Older adults with cognitive decline have reduced functional independence and quality of life, and are at greater risk for developing dementia. Therefore, identifying biomarkers that can be easily assessed within the clinical setting and predict cognitive decline is important. Early recognition of cognitive decline could promote timely implementation of preventive strategies. We included 89 community-dwelling adults aged 70 years and older in our study, and collected 32 measures of physical function, health status and cognitive function at baseline. We utilized an L1-L2 regularized regression model (elastic net) to identify which of the 32 baseline measures were strongly predictive of cognitive function after one year. We built three linear regression models: 1) based on baseline cognitive function, 2) based on variables consistently selected in every cross-validation loop, and 3) a full model based on all the 32 variables. Each of these models was carefully tested with nested cross-validation. Our model with the six variables consistently selected in every cross-validation loop had a mean squared prediction error of 7.47. This number was smaller than that of the full model (115.33) and the model with baseline cognitive function (7.98). Our model explained 47% of the variance in cognitive function after one year. We built a parsimonious model based on a selected set of six physical function and health status measures strongly predictive of cognitive function after one year. In addition to reducing the complexity of the model without changing the model significantly, our model with the top variables improved the mean prediction error and R-squared. These six physical function and health status measures can be easily implemented in a clinical setting.

Trait impulsivity predicts D-KEFS tower test performance in university students.

PubMed

Lyvers, Michael; Basch, Vanessa; Duff, Helen; Edwards, Mark S

2015-01-01

The present study examined a widely used self-report index of trait impulsiveness in relation to performance on a well-known neuropsychological executive function test in 70 university undergraduate students (50 women, 20 men) aged 18 to 24 years old. Participants completed the Barratt Impulsiveness Scale (BIS-11) and the Frontal Systems Behavior Scale (FrSBe), after which they performed the Tower Test of the Delis-Kaplan Executive Function System. Hierarchical linear regression showed that after controlling for gender, current alcohol consumption, age at onset of weekly alcohol use, and FrSBe scores, BIS-11 significantly predicted Tower Test Achievement scores, β = -.44, p < .01. The results indicate that self-reported impulsiveness is associated with poorer executive cognitive performance even in a sample likely to be characterized by relatively high general cognitive functioning (i.e., university students). The results also support the role of inhibition as a key aspect of executive task performance. Elevated scores on the BIS-11 and FrSBe are known to be linked to risky drinking in young adults as confirmed in this sample; however, only BIS-11 predicted Tower Test performance.

Prediction of recovery of motor function after stroke.

PubMed

Stinear, Cathy

2010-12-01

Stroke is a leading cause of disability. The ability to live independently after stroke depends largely on the reduction of motor impairment and the recovery of motor function. Accurate prediction of motor recovery assists rehabilitation planning and supports realistic goal setting by clinicians and patients. Initial impairment is negatively related to degree of recovery, but inter-individual variability makes accurate prediction difficult. Neuroimaging and neurophysiological assessments can be used to measure the extent of stroke damage to the motor system and predict subsequent recovery of function, but these techniques are not yet used routinely. The use of motor impairment scores and neuroimaging has been refined by two recent studies in which these investigations were used at multiple time points early after stroke. Voluntary finger extension and shoulder abduction within 5 days of stroke predicted subsequent recovery of upper-limb function. Diffusion-weighted imaging within 7 days detected the effects of stroke on caudal motor pathways and was predictive of lasting motor impairment. Thus, investigations done soon after stroke had good prognostic value. The potential prognostic value of cortical activation and neural plasticity has been explored for the first time by two recent studies. Functional MRI detected a pattern of cortical activation at the acute stage that was related to subsequent reduction in motor impairment. Transcranial magnetic stimulation enabled measurement of neural plasticity in the primary motor cortex, which was related to subsequent disability. These studies open interesting new lines of enquiry. WHERE NEXT?: The accuracy of prediction might be increased by taking into account the motor system's capacity for functional reorganisation in response to therapy, in addition to the extent of stroke-related damage. Improved prognostic accuracy could also be gained by combining simple tests of motor impairment with neuroimaging, genotyping, and

Prediction and Testing of Biological Networks Underlying Intestinal Cancer

PubMed Central

Mariadason, John M.; Wang, Donghai; Augenlicht, Leonard H.; Chance, Mark R.

2010-01-01

Colorectal cancer progresses through an accumulation of somatic mutations, some of which reside in so-called “driver” genes that provide a growth advantage to the tumor. To identify points of intersection between driver gene pathways, we implemented a network analysis framework using protein interactions to predict likely connections – both precedented and novel – between key driver genes in cancer. We applied the framework to find significant connections between two genes, Apc and Cdkn1a (p21), known to be synergistic in tumorigenesis in mouse models. We then assessed the functional coherence of the resulting Apc-Cdkn1a network by engineering in vivo single node perturbations of the network: mouse models mutated individually at Apc (Apc1638N+/−) or Cdkn1a (Cdkn1a−/−), followed by measurements of protein and gene expression changes in intestinal epithelial tissue. We hypothesized that if the predicted network is biologically coherent (functional), then the predicted nodes should associate more specifically with dysregulated genes and proteins than stochastically selected genes and proteins. The predicted Apc-Cdkn1a network was significantly perturbed at the mRNA-level by both single gene knockouts, and the predictions were also strongly supported based on physical proximity and mRNA coexpression of proteomic targets. These results support the functional coherence of the proposed Apc-Cdkn1a network and also demonstrate how network-based predictions can be statistically tested using high-throughput biological data. PMID:20824133

Generating linear regression model to predict motor functions by use of laser range finder during TUG.

PubMed

Adachi, Daiki; Nishiguchi, Shu; Fukutani, Naoto; Hotta, Takayuki; Tashiro, Yuto; Morino, Saori; Shirooka, Hidehiko; Nozaki, Yuma; Hirata, Hinako; Yamaguchi, Moe; Yorozu, Ayanori; Takahashi, Masaki; Aoyama, Tomoki

2017-05-01

The purpose of this study was to investigate which spatial and temporal parameters of the Timed Up and Go (TUG) test are associated with motor function in elderly individuals. This study included 99 community-dwelling women aged 72.9 ± 6.3 years. Step length, step width, single support time, variability of the aforementioned parameters, gait velocity, cadence, reaction time from starting signal to first step, and minimum distance between the foot and a marker placed to 3 in front of the chair were measured using our analysis system. The 10-m walk test, five times sit-to-stand (FTSTS) test, and one-leg standing (OLS) test were used to assess motor function. Stepwise multivariate linear regression analysis was used to determine which TUG test parameters were associated with each motor function test. Finally, we calculated a predictive model for each motor function test using each regression coefficient. In stepwise linear regression analysis, step length and cadence were significantly associated with the 10-m walk test, FTSTS and OLS test. Reaction time was associated with the FTSTS test, and step width was associated with the OLS test. Each predictive model showed a strong correlation with the 10-m walk test and OLS test (P < 0.01), which was not significant higher correlation than TUG test time. We showed which TUG test parameters were associated with each motor function test. Moreover, the TUG test time regarded as the lower extremity function and mobility has strong predictive ability in each motor function test. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

Plateletworks platelet function test compared to the thromboelastograph for prediction of postoperative outcomes.

PubMed

Ostrowsky, Jacob; Foes, Jennifer; Warchol, Mark; Tsarovsky, Gary; Blay, Jessica

2004-06-01

Approximately 3.5 million units of platelets are transfused in the United States each year to patients undergoing open-heart surgery with cardiopulmonary bypass (CPB). CPB is a known contributor to platelet loss and platelet dysfunction leading to disruption of hemostasis. Impaired hemostasis results in excess bleeding in 5-25% of all patients undergoing CPB. For this reason, it may be beneficial to measure platelet number and function in these patients. The purpose of this study was to compare the Plateletworks platelet function analyzer to the thromboelastograph (TEG) in predicting postoperatiave hemostatic outcomes as measured by blood product use and chest tube (CT) drainage. This study consisted of 35 adult patients undergoing cardiac surgery with cardiopulmonary bypass at Rush-Presbyterian-Saint Luke's Medical Center (RPSLMC). The Plateletworks and TEG tests were performed preoperatively, after protamine was given, and 24 hours postoperatively on all patients. Plateletworks demonstrated a statistically significant change in platelet function as shown by the adenosine diphosphate (ADP) reagent tube from the preoperative period to the removal of the aortic cross clamp (p = .011). The TEG did not demonstrate a significant change in the k-time and maximum amplitude (MA), but did show a significant change in the alpha-angle from the pre-operative to postoperatiave sample (p = .035). A correlation was found between Plateletworks collagen reagent tubes preoperatively and CT drainage (p = .048, r -0.324). No statistical correlation was established between TEG parameters and CT drainage at any time interval. TEG preoperative MA showed a correlation to receipt of blood products (p = .016). When comparing the Plateletworks to the TEG in this study, the Plateletworks system was a more useful predictor of blood product use and chest tube drainage.

Predictive Control of Speededness in Adaptive Testing

ERIC Educational Resources Information Center

van der Linden, Wim J.

2009-01-01

An adaptive testing method is presented that controls the speededness of a test using predictions of the test takers' response times on the candidate items in the pool. Two different types of predictions are investigated: posterior predictions given the actual response times on the items already administered and posterior predictions that use the…

A function approximation approach to anomaly detection in propulsion system test data

NASA Technical Reports Server (NTRS)

Whitehead, Bruce A.; Hoyt, W. A.

1993-01-01

Ground test data from propulsion systems such as the Space Shuttle Main Engine (SSME) can be automatically screened for anomalies by a neural network. The neural network screens data after being trained with nominal data only. Given the values of 14 measurements reflecting external influences on the SSME at a given time, the neural network predicts the expected nominal value of a desired engine parameter at that time. We compared the ability of three different function-approximation techniques to perform this nominal value prediction: a novel neural network architecture based on Gaussian bar basis functions, a conventional back propagation neural network, and linear regression. These three techniques were tested with real data from six SSME ground tests containing two anomalies. The basis function network trained more rapidly than back propagation. It yielded nominal predictions with, a tight enough confidence interval to distinguish anomalous deviations from the nominal fluctuations in an engine parameter. Since the function-approximation approach requires nominal training data only, it is capable of detecting unknown classes of anomalies for which training data is not available.

Biological and functional relevance of CASP predictions.

PubMed

Liu, Tianyun; Ish-Shalom, Shirbi; Torng, Wen; Lafita, Aleix; Bock, Christian; Mort, Matthew; Cooper, David N; Bliven, Spencer; Capitani, Guido; Mooney, Sean D; Altman, Russ B

2018-03-01

Our goal is to answer the question: compared with experimental structures, how useful are predicted models for functional annotation? We assessed the functional utility of predicted models by comparing the performances of a suite of methods for functional characterization on the predictions and the experimental structures. We identified 28 sites in 25 protein targets to perform functional assessment. These 28 sites included nine sites with known ligand binding (holo-sites), nine sites that are expected or suggested by experimental authors for small molecule binding (apo-sites), and Ten sites containing important motifs, loops, or key residues with important disease-associated mutations. We evaluated the utility of the predictions by comparing their microenvironments to the experimental structures. Overall structural quality correlates with functional utility. However, the best-ranked predictions (global) may not have the best functional quality (local). Our assessment provides an ability to discriminate between predictions with high structural quality. When assessing ligand-binding sites, most prediction methods have higher performance on apo-sites than holo-sites. Some servers show consistently high performance for certain types of functional sites. Finally, many functional sites are associated with protein-protein interaction. We also analyzed biologically relevant features from the protein assemblies of two targets where the active site spanned the protein-protein interface. For the assembly targets, we find that the features in the models are mainly determined by the choice of template. © 2017 The Authors Proteins: Structure, Function and Bioinformatics Published by Wiley Periodicals, Inc.

Text Mining Improves Prediction of Protein Functional Sites

PubMed Central

Cohn, Judith D.; Ravikumar, Komandur E.

2012-01-01

We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions. PMID:22393388

Predicting individual contrast sensitivity functions from acuity and letter contrast sensitivity measurements

PubMed Central

Thurman, Steven M.; Davey, Pinakin Gunvant; McCray, Kaydee Lynn; Paronian, Violeta; Seitz, Aaron R.

2016-01-01

Contrast sensitivity (CS) is widely used as a measure of visual function in both basic research and clinical evaluation. There is conflicting evidence on the extent to which measuring the full contrast sensitivity function (CSF) offers more functionally relevant information than a single measurement from an optotype CS test, such as the Pelli–Robson chart. Here we examine the relationship between functional CSF parameters and other measures of visual function, and establish a framework for predicting individual CSFs with effectively a zero-parameter model that shifts a standard-shaped template CSF horizontally and vertically according to independent measurements of high contrast acuity and letter CS, respectively. This method was evaluated for three different CSF tests: a chart test (CSV-1000), a computerized sine-wave test (M&S Sine Test), and a recently developed adaptive test (quick CSF). Subjects were 43 individuals with healthy vision or impairment too mild to be considered low vision (acuity range of −0.3 to 0.34 logMAR). While each test demands a slightly different normative template, results show that individual subject CSFs can be predicted with roughly the same precision as test–retest repeatability, confirming that individuals predominantly differ in terms of peak CS and peak spatial frequency. In fact, these parameters were sufficiently related to empirical measurements of acuity and letter CS to permit accurate estimation of the entire CSF of any individual with a deterministic model (zero free parameters). These results demonstrate that in many cases, measuring the full CSF may provide little additional information beyond letter acuity and contrast sensitivity. PMID:28006065

Biological and functional relevance of CASP predictions

PubMed Central

Liu, Tianyun; Ish‐Shalom, Shirbi; Torng, Wen; Lafita, Aleix; Bock, Christian; Mort, Matthew; Cooper, David N; Bliven, Spencer; Capitani, Guido; Mooney, Sean D.

2017-01-01

Abstract Our goal is to answer the question: compared with experimental structures, how useful are predicted models for functional annotation? We assessed the functional utility of predicted models by comparing the performances of a suite of methods for functional characterization on the predictions and the experimental structures. We identified 28 sites in 25 protein targets to perform functional assessment. These 28 sites included nine sites with known ligand binding (holo‐sites), nine sites that are expected or suggested by experimental authors for small molecule binding (apo‐sites), and Ten sites containing important motifs, loops, or key residues with important disease‐associated mutations. We evaluated the utility of the predictions by comparing their microenvironments to the experimental structures. Overall structural quality correlates with functional utility. However, the best‐ranked predictions (global) may not have the best functional quality (local). Our assessment provides an ability to discriminate between predictions with high structural quality. When assessing ligand‐binding sites, most prediction methods have higher performance on apo‐sites than holo‐sites. Some servers show consistently high performance for certain types of functional sites. Finally, many functional sites are associated with protein‐protein interaction. We also analyzed biologically relevant features from the protein assemblies of two targets where the active site spanned the protein‐protein interface. For the assembly targets, we find that the features in the models are mainly determined by the choice of template. PMID:28975675

Predicting cognitive function of the Malaysian elderly: a structural equation modelling approach.

PubMed

Foong, Hui Foh; Hamid, Tengku Aizan; Ibrahim, Rahimah; Haron, Sharifah Azizah; Shahar, Suzana

2018-01-01

The aim of this study was to identify the predictors of elderly's cognitive function based on biopsychosocial and cognitive reserve perspectives. The study included 2322 community-dwelling elderly in Malaysia, randomly selected through a multi-stage proportional cluster random sampling from Peninsular Malaysia. The elderly were surveyed on socio-demographic information, biomarkers, psychosocial status, disability, and cognitive function. A biopsychosocial model of cognitive function was developed to test variables' predictive power on cognitive function. Statistical analyses were performed using SPSS (version 15.0) in conjunction with Analysis of Moment Structures Graphics (AMOS 7.0). The estimated theoretical model fitted the data well. Psychosocial stress and metabolic syndrome (MetS) negatively predicted cognitive function and psychosocial stress appeared as a main predictor. Socio-demographic characteristics, except gender, also had significant effects on cognitive function. However, disability failed to predict cognitive function. Several factors together may predict cognitive function in the Malaysian elderly population, and the variance accounted for it is large enough to be considered substantial. Key factor associated with the elderly's cognitive function seems to be psychosocial well-being. Thus, psychosocial well-being should be included in the elderly assessment, apart from medical conditions, both in clinical and community setting.

Hydrological-niche models predict water plant functional group distributions in diverse wetland types.

PubMed

Deane, David C; Nicol, Jason M; Gehrig, Susan L; Harding, Claire; Aldridge, Kane T; Goodman, Abigail M; Brookes, Justin D

2017-06-01

Human use of water resources threatens environmental water supplies. If resource managers are to develop policies that avoid unacceptable ecological impacts, some means to predict ecosystem response to changes in water availability is necessary. This is difficult to achieve at spatial scales relevant for water resource management because of the high natural variability in ecosystem hydrology and ecology. Water plant functional groups classify species with similar hydrological niche preferences together, allowing a qualitative means to generalize community responses to changes in hydrology. We tested the potential for functional groups in making quantitative prediction of water plant functional group distributions across diverse wetland types over a large geographical extent. We sampled wetlands covering a broad range of hydrogeomorphic and salinity conditions in South Australia, collecting both hydrological and floristic data from 687 quadrats across 28 wetland hydrological gradients. We built hydrological-niche models for eight water plant functional groups using a range of candidate models combining different surface inundation metrics. We then tested the predictive performance of top-ranked individual and averaged models for each functional group. Cross validation showed that models achieved acceptable predictive performance, with correct classification rates in the range 0.68-0.95. Model predictions can be made at any spatial scale that hydrological data are available and could be implemented in a geographical information system. We show the response of water plant functional groups to inundation is consistent enough across diverse wetland types to quantify the probability of hydrological impacts over regional spatial scales. © 2017 by the Ecological Society of America.

Hierarchical Ensemble Methods for Protein Function Prediction

PubMed Central

2014-01-01

Protein function prediction is a complex multiclass multilabel classification problem, characterized by multiple issues such as the incompleteness of the available annotations, the integration of multiple sources of high dimensional biomolecular data, the unbalance of several functional classes, and the difficulty of univocally determining negative examples. Moreover, the hierarchical relationships between functional classes that characterize both the Gene Ontology and FunCat taxonomies motivate the development of hierarchy-aware prediction methods that showed significantly better performances than hierarchical-unaware “flat” prediction methods. In this paper, we provide a comprehensive review of hierarchical methods for protein function prediction based on ensembles of learning machines. According to this general approach, a separate learning machine is trained to learn a specific functional term and then the resulting predictions are assembled in a “consensus” ensemble decision, taking into account the hierarchical relationships between classes. The main hierarchical ensemble methods proposed in the literature are discussed in the context of existing computational methods for protein function prediction, highlighting their characteristics, advantages, and limitations. Open problems of this exciting research area of computational biology are finally considered, outlining novel perspectives for future research. PMID:25937954

Which Neuropsychological Tests Predict Progression to Alzheimer’s Disease in Hispanics?

PubMed Central

Weissberger, Gali H.; Salmon, David P.; Bondi, Mark W.; Gollan, Tamar H.

2013-01-01

Objective To investigate which neuropsychological tests predict eventual progression to Alzheimer’s disease (AD) in both Hispanic and non-Hispanic individuals. Although our approach was exploratory, we predicted that tests that underestimate cognitive ability in healthy aging Hispanics might not be sensitive to future cognitive decline in this cultural group. Method We compared first-year data of 22 older adults (11 Hispanic) who were diagnosed as cognitively normal but eventually developed AD (decliners), to 60 age- and education-matched controls (27 Hispanic) who remained cognitively normal. To identify tests that may be culturally biased in our sample, we compared Hispanic with non-Hispanic controls on all tests and asked which tests were sensitive to future decline in each cultural group. Results Compared to age-, education-, and gender-matched non-Hispanic controls, Hispanic controls obtained lower scores on tests of language, executive function, and some measures of global cognition. Consistent with our predictions, some tests identified non-Hispanic, but not Hispanic, decliners (vocabulary, semantic fluency). Contrary to our predictions, a number of tests on which Hispanics obtained lower scores than non-Hispanics nevertheless predicted eventual progression to AD in both cultural groups (e.g., Boston Naming Test [BNT], Trails A and B). Conclusions Cross-cultural variation in test sensitivity to decline may reflect greater resistance of medium difficulty items to decline and bilingual advantages that initially protect Hispanics against some aspects of cognitive decline commonly observed in non-Hispanics with preclinical AD. These findings highlight a need for further consideration of cross-cultural differences in neuropsychological test performance and development of culturally unbiased measures. PMID:23688216

PRISM offers a comprehensive genomic approach to transcription factor function prediction

PubMed Central

Wenger, Aaron M.; Clarke, Shoa L.; Guturu, Harendra; Chen, Jenny; Schaar, Bruce T.; McLean, Cory Y.; Bejerano, Gill

2013-01-01

The human genome encodes 1500–2000 different transcription factors (TFs). ChIP-seq is revealing the global binding profiles of a fraction of TFs in a fraction of their biological contexts. These data show that the majority of TFs bind directly next to a large number of context-relevant target genes, that most binding is distal, and that binding is context specific. Because of the effort and cost involved, ChIP-seq is seldom used in search of novel TF function. Such exploration is instead done using expression perturbation and genetic screens. Here we propose a comprehensive computational framework for transcription factor function prediction. We curate 332 high-quality nonredundant TF binding motifs that represent all major DNA binding domains, and improve cross-species conserved binding site prediction to obtain 3.3 million conserved, mostly distal, binding site predictions. We combine these with 2.4 million facts about all human and mouse gene functions, in a novel statistical framework, in search of enrichments of particular motifs next to groups of target genes of particular functions. Rigorous parameter tuning and a harsh null are used to minimize false positives. Our novel PRISM (predicting regulatory information from single motifs) approach obtains 2543 TF function predictions in a large variety of contexts, at a false discovery rate of 16%. The predictions are highly enriched for validated TF roles, and 45 of 67 (67%) tested binding site regions in five different contexts act as enhancers in functionally matched cells. PMID:23382538

A scoring function based on solvation thermodynamics for protein structure prediction

PubMed Central

Du, Shiqiao; Harano, Yuichi; Kinoshita, Masahiro; Sakurai, Minoru

2012-01-01

We predict protein structure using our recently developed free energy function for describing protein stability, which is focused on solvation thermodynamics. The function is combined with the current most reliable sampling methods, i.e., fragment assembly (FA) and comparative modeling (CM). The prediction is tested using 11 small proteins for which high-resolution crystal structures are available. For 8 of these proteins, sequence similarities are found in the database, and the prediction is performed with CM. Fairly accurate models with average Cα root mean square deviation (RMSD) ∼ 2.0 Å are successfully obtained for all cases. For the rest of the target proteins, we perform the prediction following FA protocols. For 2 cases, we obtain predicted models with an RMSD ∼ 3.0 Å as the best-scored structures. For the other case, the RMSD remains larger than 7 Å. For all the 11 target proteins, our scoring function identifies the experimentally determined native structure as the best structure. Starting from the predicted structure, replica exchange molecular dynamics is performed to further refine the structures. However, we are unable to improve its RMSD toward the experimental structure. The exhaustive sampling by coarse-grained normal mode analysis around the native structures reveals that our function has a linear correlation with RMSDs < 3.0 Å. These results suggest that the function is quite reliable for the protein structure prediction while the sampling method remains one of the major limiting factors in it. The aspects through which the methodology could further be improved are discussed. PMID:27493529

Sensitivity and specificity of subacute computerized neurocognitive testing and symptom evaluation in predicting outcomes after sports-related concussion.

PubMed

Lau, Brian C; Collins, Michael W; Lovell, Mark R

2011-06-01

Concussions affect an estimated 136 000 high school athletes yearly. Computerized neurocognitive testing has been shown to be appropriately sensitive and specific in diagnosing concussions, but no studies have assessed its utility to predict length of recovery. Determining prognosis during subacute recovery after sports concussion will help clinicians more confidently address return-to-play and academic decisions. To quantify the prognostic ability of computerized neurocognitive testing in combination with symptoms during the subacute recovery phase from sports-related concussion. Cohort study (prognosis); Level of evidence, 2. In sum, 108 male high school football athletes completed a computer-based neurocognitive test battery within 2.23 days of injury and were followed until returned to play as set by international guidelines. Athletes were grouped into protracted recovery (>14 days; n = 50) or short-recovery (≤14 days; n = 58). Separate discriminant function analyses were performed using total symptom score on Post-Concussion Symptom Scale, symptom clusters (migraine, cognitive, sleep, neuropsychiatric), and Immediate Postconcussion Assessment and Cognitive Testing neurocognitive scores (verbal memory, visual memory, reaction time, processing speed). Multiple discriminant function analyses revealed that the combination of 4 symptom clusters and 4 neurocognitive composite scores had the highest sensitivity (65.22%), specificity (80.36%), positive predictive value (73.17%), and negative predictive value (73.80%) in predicting protracted recovery. Discriminant function analyses of total symptoms on the Post-Concussion Symptom Scale alone had a sensitivity of 40.81%; specificity, 79.31%; positive predictive value, 62.50%; and negative predictive value, 61.33%. The 4 symptom clusters alone discriminant function analyses had a sensitivity of 46.94%; specificity, 77.20%; positive predictive value, 63.90%; and negative predictive value, 62.86%. Discriminant function

Lifestyle Markers Predict Cognitive Function.

PubMed

Masley, Steven C; Roetzheim, Richard; Clayton, Gwendolyn; Presby, Angela; Sundberg, Kelley; Masley, Lucas V

2017-01-01

Rates of mild cognitive impairment and Alzheimer's disease are increasing rapidly. None of the current treatment regimens for Alzheimer's disease are effective in arresting progression. Lifestyle choices may prevent cognitive decline. This study aims to clarify which factors best predict cognitive function. This was a prospective cross-sectional analysis of 799 men and women undergoing health and cognitive testing every 1 to 3 years at an outpatient center. This study utilizes data collected from the first patient visit. Participant ages were 18 to 88 (mean = 50.7) years and the sample was 26.6% female and 73.4% male. Measurements were made of body composition, fasting laboratory and anthropometric measures, strength and aerobic fitness, nutrient and dietary intake, and carotid intimal media thickness (IMT). Each participant was tested with a computerized neurocognitive test battery. Cognitive outcomes were assessed in bivariate analyses using t-tests and correlation coefficients and in multivariable analysis (controlling for age) using multiple linear regression. The initial bivariate analyses showed better Neurocognitive Index (NCI) scores with lower age, greater fitness scores (push-up strength, VO 2 max, and exercise duration during treadmill testing), and lower fasting glucose levels. Better cognitive flexibility scores were also noted with younger age, lower systolic blood pressure, lower body fat, lower carotid IMT scores, greater fitness, and higher alcohol intake. After controlling for age, factors that remained associated with better NCI scores include no tobacco use, lower fasting glucose levels, and better fitness (aerobic and strength). Higher cognitive flexibility scores remained associated with greater aerobic and strength fitness, lower body fat, and higher intake of alcohol. Modifiable biomarkers that impact cognitive performance favorably include greater aerobic fitness and strength, lower blood sugar levels, greater alcohol intake, lower body

Predictive value and construct validity of the work functioning screener-healthcare (WFS-H).

PubMed

Boezeman, Edwin J; Nieuwenhuijsen, Karen; Sluiter, Judith K

2016-05-25

To test the predictive value and convergent construct validity of a 6-item work functioning screener (WFS-H). Healthcare workers (249 nurses) completed a questionnaire containing the work functioning screener (WFS-H) and a work functioning instrument (NWFQ) measuring the following: cognitive aspects of task execution and general incidents, avoidance behavior, conflicts and irritation with colleagues, impaired contact with patients and their family, and level of energy and motivation. Productivity and mental health were also measured. Negative and positive predictive values, AUC values, and sensitivity and specificity were calculated to examine the predictive value of the screener. Correlation analysis was used to examine the construct validity. The screener had good predictive value, since the results showed that a negative screener score is a strong indicator of work functioning not hindered by mental health problems (negative predictive values: 94%-98%; positive predictive values: 21%-36%; AUC:.64-.82; sensitivity: 42%-76%; and specificity 85%-87%). The screener has good construct validity due to moderate, but significant (p<.001), associations with productivity (r=.51), mental health (r=.48), and distress (r=.47). The screener (WFS-H) had good predictive value and good construct validity. Its score offers occupational health professionals a helpful preliminary insight into the work functioning of healthcare workers.

Predictive capabilities of preoperative and postoperative pulmonary function tests in delayed repair of congenital diaphragmatic hernia.

PubMed

Tracy, T F; Bailey, P V; Sadiq, F; Noguchi, A; Silen, M L; Weber, T R

1994-02-01

To improve the survival of newborns with congenital diaphragmatic hernia (CHD), preoperative stabilization with conventional ventilatory therapy and extracorporeal membrane oxygenation (ECMO) have been used. Measurements that quantify pulmonary function may allow an accurate assessment of lethal pulmonary hypoplasia and predict outcome. Pulmonary function tests (PFTs) were obtained in 20 infants preoperatively and postoperatively; these included measurements of compliance, dynamic compliance, and tidal volume. Overall survival was 75%. Six surviving infants were initially managed with ventilator therapy alone, followed by repair (group 1). The remaining 14 patients, who were moribund at presentation or whose initial ventilator therapy failed, were placed on ECMO and received repair during bypass; nine survived (group 2), and five died (group 3). Compliance, dynamic compliance, and tidal volume obtained at initial presentation and immediately preoperatively were significantly higher for group 1 as compared with groups 2 and 3. Infants whose initial compliance was greater than 0.25 mL/cm H2O/kg and initial tidal volume was greater than 3.5 mL/kg did not require ECMO. Ultimate improvement in compliance was noted in 5 of 6 patients in group 1, 8 of 8 patients in group 2, and 5 of 5 in group 3. This improvement followed an initial decline in compliance in 9 of 14 survivors, from 15% to 76%. All six patients in group 1 had tidal volumes of more than 4 mL/kg, as did 7 of 9 patients in group 2. Only one patient among the ECMO nonsurvivors (group 3) had a postoperative tidal volume of this magnitude. These data suggest that initial PFTs may predict which infants will require ECMO.(ABSTRACT TRUNCATED AT 250 WORDS)

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning

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

He, Zhili; Zhang, Ping; Wu, Linwei

Contamination from anthropogenic activities has significantly impacted Earth’s biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminantsmore » would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly (P < 0.05) as uranium or nitrate increased, and their changes could be used to successfully predict uranium and nitrate contamination and ecosystem functioning. Here, this study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning.« less

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning

PubMed Central

Zhang, Ping; Wu, Linwei; Rocha, Andrea M.; Shi, Zhou; Wu, Bo; Qin, Yujia; Wang, Jianjun; Yan, Qingyun; Curtis, Daniel; Ning, Daliang; Van Nostrand, Joy D.; Wu, Liyou; Watson, David B.; Adams, Michael W. W.; Alm, Eric J.; Adams, Paul D.; Arkin, Adam P.

2018-01-01

ABSTRACT Contamination from anthropogenic activities has significantly impacted Earth’s biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly (P < 0.05) as uranium or nitrate increased, and their changes could be used to successfully predict uranium and nitrate contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning. PMID:29463661

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning

DOE PAGES

He, Zhili; Zhang, Ping; Wu, Linwei; ...

2018-02-20

Contamination from anthropogenic activities has significantly impacted Earth’s biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminantsmore » would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly (P < 0.05) as uranium or nitrate increased, and their changes could be used to successfully predict uranium and nitrate contamination and ecosystem functioning. Here, this study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning.« less

Dynamic prediction in functional concurrent regression with an application to child growth.

PubMed

Leroux, Andrew; Xiao, Luo; Crainiceanu, Ciprian; Checkley, William

2018-04-15

In many studies, it is of interest to predict the future trajectory of subjects based on their historical data, referred to as dynamic prediction. Mixed effects models have traditionally been used for dynamic prediction. However, the commonly used random intercept and slope model is often not sufficiently flexible for modeling subject-specific trajectories. In addition, there may be useful exposures/predictors of interest that are measured concurrently with the outcome, complicating dynamic prediction. To address these problems, we propose a dynamic functional concurrent regression model to handle the case where both the functional response and the functional predictors are irregularly measured. Currently, such a model cannot be fit by existing software. We apply the model to dynamically predict children's length conditional on prior length, weight, and baseline covariates. Inference on model parameters and subject-specific trajectories is conducted using the mixed effects representation of the proposed model. An extensive simulation study shows that the dynamic functional regression model provides more accurate estimation and inference than existing methods. Methods are supported by fast, flexible, open source software that uses heavily tested smoothing techniques. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Predicting the Functional Impact of KCNQ1 Variants of Unknown Significance.

PubMed

Li, Bian; Mendenhall, Jeffrey L; Kroncke, Brett M; Taylor, Keenan C; Huang, Hui; Smith, Derek K; Vanoye, Carlos G; Blume, Jeffrey D; George, Alfred L; Sanders, Charles R; Meiler, Jens

2017-10-01

An emerging standard-of-care for long-QT syndrome uses clinical genetic testing to identify genetic variants of the KCNQ1 potassium channel. However, interpreting results from genetic testing is confounded by the presence of variants of unknown significance for which there is inadequate evidence of pathogenicity. In this study, we curated from the literature a high-quality set of 107 functionally characterized KCNQ1 variants. Based on this data set, we completed a detailed quantitative analysis on the sequence conservation patterns of subdomains of KCNQ1 and the distribution of pathogenic variants therein. We found that conserved subdomains generally are critical for channel function and are enriched with dysfunctional variants. Using this experimentally validated data set, we trained a neural network, designated Q1VarPred, specifically for predicting the functional impact of KCNQ1 variants of unknown significance. The estimated predictive performance of Q1VarPred in terms of Matthew's correlation coefficient and area under the receiver operating characteristic curve were 0.581 and 0.884, respectively, superior to the performance of 8 previous methods tested in parallel. Q1VarPred is publicly available as a web server at http://meilerlab.org/q1varpred. Although a plethora of tools are available for making pathogenicity predictions over a genome-wide scale, previous tools fail to perform in a robust manner when applied to KCNQ1. The contrasting and favorable results for Q1VarPred suggest a promising approach, where a machine-learning algorithm is tailored to a specific protein target and trained with a functionally validated data set to calibrate informatics tools. © 2017 American Heart Association, Inc.

Liver function tests

MedlinePlus

Liver function tests are common tests that are used to see how well the liver is working. Tests include: ... E, Bowne WB, Bluth MH. Evaluation of liver function. In: McPherson RA, Pincus MR, eds. Henry's Clinical ...

Liver Function Tests

MedlinePlus

... food, store energy, and remove poisons. Liver function tests are blood tests that check to see how well your liver ... hepatitis and cirrhosis. You may have liver function tests as part of a regular checkup. Or you ...

Kidney function tests

MedlinePlus

Kidney function tests are common lab tests used to evaluate how well the kidneys are working. Such tests include: ... Oh MS, Briefel G. Evaluation of renal function, water, electrolytes ... and Management by Laboratory Methods . 23rd ed. Philadelphia, ...

Wideband acoustic reflex test in a test battery to predict middle-ear dysfunction

PubMed Central

Keefe, Douglas H.; Fitzpatrick, Denis; Liu, Yi-Wen; Sanford, Chris A.; Gorga, Michael P.

2013-01-01

A wideband (WB) aural acoustical test battery of middle-ear status, including acoustic-reflex thresholds (ARTs) and acoustic-transfer functions (ATFs, i.e., absorbance and admittance) was hypothesized to be more accurate than 1-kHz tympanometry in classifying ears that pass or refer on a newborn hearing screening (NHS) protocol based on otoacoustic emissions. Assessment of middle-ear status may improve NHS programs by identifying conductive dysfunction and cases in which auditory neuropathy exists. Ipsilateral ARTs were assessed with a stimulus including four broadband-noise or tonal activator pulses alternating with five clicks presented before, between and after the pulses. The reflex shift was defined as the difference between final and initial click responses. ARTs were measured using maximum likelihood both at low frequencies (0.8–2.8 kHz) and high (2.8–8 kHz). The median low-frequency ART was elevated by 24 dB in NHS refers compared to passes. An optimal combination of ATF and ART tests performed better than either test alone in predicting NHS outcomes, and WB tests performed better than 1-kHz tympanometry. Medial olivocochlear efferent shifts in cochlear function may influence ARs, but their presence would also be consistent with normal conductive function. Baseline clinical and WB ARTs were also compared in ipsilateral and contralateral measurements in adults. PMID:19772907

Functional test of pedotransfer functions to predict water flow and solute transport with the dual-permeability model MACRO

NASA Astrophysics Data System (ADS)

Moeys, J.; Larsbo, M.; Bergström, L.; Brown, C. D.; Coquet, Y.; Jarvis, N. J.

2012-07-01

Estimating pesticide leaching risks at the regional scale requires the ability to completely parameterise a pesticide fate model using only survey data, such as soil and land-use maps. Such parameterisations usually rely on a set of lookup tables and (pedo)transfer functions, relating elementary soil and site properties to model parameters. The aim of this paper is to describe and test a complete set of parameter estimation algorithms developed for the pesticide fate model MACRO, which accounts for preferential flow in soil macropores. We used tracer monitoring data from 16 lysimeter studies, carried out in three European countries, to evaluate the ability of MACRO and this "blind parameterisation" scheme to reproduce measured solute leaching at the base of each lysimeter. We focused on the prediction of early tracer breakthrough due to preferential flow, because this is critical for pesticide leaching. We then calibrated a selected number of parameters in order to assess to what extent the prediction of water and solute leaching could be improved. Our results show that water flow was generally reasonably well predicted (median model efficiency, ME, of 0.42). Although the general pattern of solute leaching was reproduced well by the model, the overall model efficiency was low (median ME = -0.26) due to errors in the timing and magnitude of some peaks. Preferential solute leaching at early pore volumes was also systematically underestimated. Nonetheless, the ranking of soils according to solute loads at early pore volumes was reasonably well estimated (concordance correlation coefficient, CCC, between 0.54 and 0.72). Moreover, we also found that ignoring macropore flow leads to a significant deterioration in the ability of the model to reproduce the observed leaching pattern, and especially the early breakthrough in some soils. Finally, the calibration procedure showed that improving the estimation of solute transport parameters is probably more important than the

Functional MR imaging or Wada test: which is the better predictor of individual postoperative memory outcome?

PubMed

Dupont, Sophie; Duron, Emmanuelle; Samson, Séverine; Denos, Marisa; Volle, Emmanuelle; Delmaire, Christine; Navarro, Vincent; Chiras, Jacques; Lehéricy, Stéphane; Samson, Yves; Baulac, Michel

2010-04-01

To retrospectively determine whether blood oxygen level-dependent functional magnetic resonance (MR) imaging can aid prediction of postoperative memory changes in epileptic patients after temporal lobe surgery. This study was approved by the local ethics committee, and informed consent was obtained from all patients. Data were analyzed from 25 patients (12 women, 13 men; age range, 19-52 years) with refractory epilepsy in whom temporal lobe surgery was performed after they underwent preoperative functional MR imaging, the Wada test, and neuropsychological testing. The functional MR imaging protocol included three different memory tasks (24-hour delayed recognition, encoding, and immediate recognition). Individual activations were measured in medial temporal lobe (MTL) regions of both hemispheres. The prognostic accuracy of functional MR imaging for prediction of postoperative memory changes was compared with the accuracy of the Wada test and preoperative neuropsychological testing by using a backward multiple regression analysis. An equation that was based on left functional MR imaging MTL activation during delayed recognition, side of the epileptic focus, and preoperative global verbal memory score was used to correctly predict worsening of verbal memory in 90% of patients. The right functional MR imaging MTL activation did not substantially correlate with the nonverbal memory outcome, which was only predicted by using the preoperative nonverbal global score. Wada test data were not good predictors of changes in either verbal or nonverbal memory. Findings suggest that functional MR imaging activation during a delayed-recognition task is a better predictor of individual postoperative verbal memory outcome than is the Wada test. RSNA, 2010

Does Executive Functioning (EF) Predict Depression in Clinic-Referred Adults?: EF Tests vs. Rating Scales

PubMed Central

Knouse, Laura E.; Barkley, Russell A.; Murphy, Kevin R.

2012-01-01

Background Deficits in executive functioning (EF) are implicated in neurobiological and cognitive-processing theories of depression. EF deficits are also associated with Attention-deficit/hyperactivity disorder (ADHD) in adults, who are also at increased risk for depressive disorders. Given debate about the ecological validity of laboratory measures of EF, we investigated the relationship between depression diagnoses and symptoms and EF as measured by both rating scales and tests in a sample of adults referred for evaluation of adult ADHD. Method Data from two groups of adults recruited from an ADHD specialty clinic were analyzed together: Adults diagnosed with ADHD (N=146) and a clinical control group of adults referred for adult ADHD assessment but not diagnosed with the disorder ADHD (N=97). EF was assessed using a rating scale of EF deficits in daily life and a battery of tests tapping various EF constructs. Depression was assessed using current and lifetime SCID diagnoses (major depression, dysthymia) and self-report symptom ratings. Results EF as assessed via rating scale predicted depression across measures even when controlling for current anxiety and impairment. Self-Management to Time and Self-Organization and Problem-Solving showed the most robust relationships. EF tests were weakly and inconsistently related to depression measures. Limitations Prospective studies are needed to rigorously evaluate EF problems as true risk factors for depressive onset. Conclusions EF problems in everyday life were important predictors of depression. Researchers and clinicians should consistently assess for the ADHD-depression comorbidity. Clinicians should consider incorporating strategies to address EF deficits when treating people with depression. PMID:22858220

Human Chorionic Gonadotropin Stimulation Test in Prepubertal Children with Micropenis Can Accurately Predict Leydig Cell Function in Pubertal or Postpubertal Adolescents.

PubMed

Ishii, Tomohiro; Matsuo, Nobutake; Sato, Seiji; Ogata, Tsutomu; Tamai, Shinya; Anzo, Makoto; Kamimaki, Tsutomu; Sasaki, Goro; Inokuchi, Mikako; Hori, Naoaki; Amano, Naoko; Narumi, Satoshi; Shibata, Hironori; Hasegawa, Tomonobu

2015-01-01

To evaluate the accuracy of the human chorionic gonadotropin (hCG) stimulation test in children with micropenis in predicting later Leydig cell function. We conducted a retrospective investigation of testosterone response to a 3-day hCG test (3,000 IU/m2/day) in prepuberty to indicate the need for hormone replacement therapy (HRT) in adolescence. Fifty Japanese boys (range, 0.8-15.4 years of age; median, 8.9) with micropenis were enrolled. Thirty-four spontaneously developed puberty and preserved the ability of testosterone production (group 1), while 16 did not develop any pubertal signs without HRT (group 2). Serum testosterone levels after the hCG test (post-hCG T) in group 2 (range, <0.05-1.1 ng/ml; median, 0.24) were significantly lower than in group 1 (range, 0.5-8.7 ng/ml; median, 2.4; p < 0.0001). Based on true positives who required continuous HRT, the area under the receiver-operating characteristics curve for post-hCG T was 0.983 [95% confidence interval (CI), 0.90-1.00]. The post-hCG T cut-off level corresponding to the Youden index was 1.1 ng/ml (95% CI, 1.0-1.1), with a sensitivity of 100.0% (95% CI, 79.4-100.0) and a specificity of 94.1% (95% CI, 80.3-99.3). The hCG test in prepubertal children with micropenis can be useful for predicting Leydig cell function in pubertal or postpubertal adolescents. The post-hCG T cut-off level of 1.1 ng/ml is recommended to screen for those who will likely require HRT for pubertal development. © 2015 S. Karger AG, Basel.

Extensive complementarity between gene function prediction methods.

PubMed

Vidulin, Vedrana; Šmuc, Tomislav; Supek, Fran

2016-12-01

The number of sequenced genomes rises steadily but we still lack the knowledge about the biological roles of many genes. Automated function prediction (AFP) is thus a necessity. We hypothesized that AFP approaches that draw on distinct genome features may be useful for predicting different types of gene functions, motivating a systematic analysis of the benefits gained by obtaining and integrating such predictions. Our pipeline amalgamates 5 133 543 genes from 2071 genomes in a single massive analysis that evaluates five established genomic AFP methodologies. While 1227 Gene Ontology (GO) terms yielded reliable predictions, the majority of these functions were accessible to only one or two of the methods. Moreover, different methods tend to assign a GO term to non-overlapping sets of genes. Thus, inferences made by diverse genomic AFP methods display a striking complementary, both gene-wise and function-wise. Because of this, a viable integration strategy is to rely on a single most-confident prediction per gene/function, rather than enforcing agreement across multiple AFP methods. Using an information-theoretic approach, we estimate that current databases contain 29.2 bits/gene of known Escherichia coli gene functions. This can be increased by up to 5.5 bits/gene using individual AFP methods or by 11 additional bits/gene upon integration, thereby providing a highly-ranking predictor on the Critical Assessment of Function Annotation 2 community benchmark. Availability of more sequenced genomes boosts the predictive accuracy of AFP approaches and also the benefit from integrating them. The individual and integrated GO predictions for the complete set of genes are available from http://gorbi.irb.hr/ CONTACT: fran.supek@irb.hrSupplementary information: Supplementary materials 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.

PREDICTION OF NONLINEAR SPATIAL FUNCTIONALS. (R827257)

EPA Science Inventory

Spatial statistical methodology can be useful in the arena of environmental regulation. Some regulatory questions may be addressed by predicting linear functionals of the underlying signal, but other questions may require the prediction of nonlinear functionals of the signal. ...

Predicting functional outcomes among college drinkers: reliability and predictive validity of the Young Adult Alcohol Consequences Questionnaire.

PubMed

Read, Jennifer P; Merrill, Jennifer E; Kahler, Christopher W; Strong, David R

2007-11-01

Heavy drinking and associated consequences are widespread among U.S. college students. Recently, Read et al. (Read, J. P., Kahler, C. W., Strong, D., & Colder, C. R. (2006). Development and preliminary validation of the Young Adult Alcohol Consequences Questionnaire. Journal of Studies on Alcohol, 67, 169-178) developed the Young Adult Alcohol Consequences Questionnaire (YAACQ) to assess the broad range of consequences that may result from heavy drinking in the college milieu. In the present study, we sought to add to the psychometric validation of this measure by employing a prospective design to examine the test-retest reliability, concurrent validity, and predictive validity of the YAACQ. We also sought to examine the utility of the YAACQ administered early in the semester in the prediction of functional outcomes later in the semester, including the persistence of heavy drinking, and academic functioning. Ninety-two college students (48 females) completed a self-report assessment battery during the first weeks of the Fall semester, and approximately one week later. Additionally, 64 subjects (37 females) participated at an optional third time point at the end of the semester. Overall, the YAACQ demonstrated strong internal consistency, test-retest reliability, and concurrent and predictive validity. YAACQ scores also were predictive of both drinking frequency, and "binge" drinking frequency. YAACQ total scores at baseline were an early indicator of academic performance later in the semester, with greater number of total consequences experienced being negatively associated with end-of-semester grade point average. Specific YAACQ subscale scores (Impaired Control, Dependence Symptoms, Blackout Drinking) showed unique prediction of persistent drinking and academic outcomes.

Validation of Skeletal Muscle cis-Regulatory Module Predictions Reveals Nucleotide Composition Bias in Functional Enhancers

PubMed Central

Kwon, Andrew T.; Chou, Alice Yi; Arenillas, David J.; Wasserman, Wyeth W.

2011-01-01

We performed a genome-wide scan for muscle-specific cis-regulatory modules (CRMs) using three computational prediction programs. Based on the predictions, 339 candidate CRMs were tested in cell culture with NIH3T3 fibroblasts and C2C12 myoblasts for capacity to direct selective reporter gene expression to differentiated C2C12 myotubes. A subset of 19 CRMs validated as functional in the assay. The rate of predictive success reveals striking limitations of computational regulatory sequence analysis methods for CRM discovery. Motif-based methods performed no better than predictions based only on sequence conservation. Analysis of the properties of the functional sequences relative to inactive sequences identifies nucleotide sequence composition can be an important characteristic to incorporate in future methods for improved predictive specificity. Muscle-related TFBSs predicted within the functional sequences display greater sequence conservation than non-TFBS flanking regions. Comparison with recent MyoD and histone modification ChIP-Seq data supports the validity of the functional regions. PMID:22144875

Single-legged Hop Tests as Predictors of Self-reported Knee Function After Anterior Cruciate Ligament Reconstruction

PubMed Central

Logerstedt, David; Grindem, Hege; Lynch, Andrew; Eitzen, Ingrid; Engebretsen, Lars; Risberg, May Arna; Axe, Michael J.; Snyder-Mackler, Lynn

2012-01-01

Background Single-legged hop tests are commonly used functional performance measures that can capture limb asymmetries in patients after anterior cruciate ligament (ACL) reconstruction. Hop tests hold potential as predictive factors of self-reported knee function in individuals after ACL reconstruction. Hypothesis Single-legged hop tests conducted preoperatively would not and 6 months after ACL reconstruction would predict self-reported knee function (International Knee Documentation Committee [IKDC] 2000) 1 year after ACL reconstruction. Study Design Cohort study (prognosis); Level of evidence, 2. Methods One hundred twenty patients who were treated with ACL reconstruction performed 4 single-legged hop tests preoperatively and 6 months after ACL reconstruction. Self-reported knee function within normal ranges was defined as IKDC 2000 scores greater than or equal to the age- and sex-specific normative 15th percentile score 1 year after surgery. Logistic regression analyses were performed to identify predictors of self-reported knee function within normal ranges. The area under the curve (AUC) from receiver operating characteristic curves was used as a measure of discriminative accuracy. Results Eighty-five patients completed single-legged hop tests 6 months after surgery and the 1-year follow-up with 68 patients classified as having self-reported knee function within normal ranges 1 year after reconstruction. The crossover hop and 6-m timed hop limb symmetry index (LSI) 6 months after ACL reconstruction were the strongest individual predictors of self-reported knee function (odds ratio, 1.09 and 1.10) and the only 2 tests in which the confidence intervals of the discriminatory accuracy (AUC) were above 0.5 (AUC = 0.68). Patients with knee function below normal ranges were over 5 times more likely of having a 6-m timed hop LSI lower than the 88% cutoff than those with knee function within normal ranges. Patients with knee function within normal ranges were 4 times

COMBREX-DB: an experiment centered database of protein function: knowledge, predictions and knowledge gaps.

PubMed

Chang, Yi-Chien; Hu, Zhenjun; Rachlin, John; Anton, Brian P; Kasif, Simon; Roberts, Richard J; Steffen, Martin

2016-01-04

The COMBREX database (COMBREX-DB; combrex.bu.edu) is an online repository of information related to (i) experimentally determined protein function, (ii) predicted protein function, (iii) relationships among proteins of unknown function and various types of experimental data, including molecular function, protein structure, and associated phenotypes. The database was created as part of the novel COMBREX (COMputational BRidges to EXperiments) effort aimed at accelerating the rate of gene function validation. It currently holds information on ∼ 3.3 million known and predicted proteins from over 1000 completely sequenced bacterial and archaeal genomes. The database also contains a prototype recommendation system for helping users identify those proteins whose experimental determination of function would be most informative for predicting function for other proteins within protein families. The emphasis on documenting experimental evidence for function predictions, and the prioritization of uncharacterized proteins for experimental testing distinguish COMBREX from other publicly available microbial genomics resources. This article describes updates to COMBREX-DB since an initial description in the 2011 NAR Database Issue. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Prediction of clinical response to drugs in ovarian cancer using the chemotherapy resistance test (CTR-test).

PubMed

Kischkel, Frank Christian; Meyer, Carina; Eich, Julia; Nassir, Mani; Mentze, Monika; Braicu, Ioana; Kopp-Schneider, Annette; Sehouli, Jalid

2017-10-27

In order to validate if the test result of the Chemotherapy Resistance Test (CTR-Test) is able to predict the resistances or sensitivities of tumors in ovarian cancer patients to drugs, the CTR-Test result and the corresponding clinical response of individual patients were correlated retrospectively. Results were compared to previous recorded correlations. The CTR-Test was performed on tumor samples from 52 ovarian cancer patients for specific chemotherapeutic drugs. Patients were treated with monotherapies or drug combinations. Resistances were classified as extreme (ER), medium (MR) or slight (SR) resistance in the CTR-Test. Combination treatment resistances were transformed by a scoring system into these classifications. Accurate sensitivity prediction was accomplished in 79% of the cases and accurate prediction of resistance in 100% of the cases in the total data set. The data set of single agent treatment and drug combination treatment were analyzed individually. Single agent treatment lead to an accurate sensitivity in 44% of the cases and the drug combination to 95% accuracy. The detection of resistances was in both cases to 100% correct. ROC curve analysis indicates that the CTR-Test result correlates with the clinical response, at least for the combination chemotherapy. Those values are similar or better than the values from a publication from 1990. Chemotherapy resistance testing in vitro via the CTR-Test is able to accurately detect resistances in ovarian cancer patients. These numbers confirm and even exceed results published in 1990. Better sensitivity detection might be caused by a higher percentage of drug combinations tested in 2012 compared to 1990. Our study confirms the functionality of the CTR-Test to plan an efficient chemotherapeutic treatment for ovarian cancer patients.

Comparative study of biodegradability prediction of chemicals using decision trees, functional trees, and logistic regression.

PubMed

Chen, Guangchao; Li, Xuehua; Chen, Jingwen; Zhang, Ya-Nan; Peijnenburg, Willie J G M

2014-12-01

Biodegradation is the principal environmental dissipation process of chemicals. As such, it is a dominant factor determining the persistence and fate of organic chemicals in the environment, and is therefore of critical importance to chemical management and regulation. In the present study, the authors developed in silico methods assessing biodegradability based on a large heterogeneous set of 825 organic compounds, using the techniques of the C4.5 decision tree, the functional inner regression tree, and logistic regression. External validation was subsequently carried out by 2 independent test sets of 777 and 27 chemicals. As a result, the functional inner regression tree exhibited the best predictability with predictive accuracies of 81.5% and 81.0%, respectively, on the training set (825 chemicals) and test set I (777 chemicals). Performance of the developed models on the 2 test sets was subsequently compared with that of the Estimation Program Interface (EPI) Suite Biowin 5 and Biowin 6 models, which also showed a better predictability of the functional inner regression tree model. The model built in the present study exhibits a reasonable predictability compared with existing models while possessing a transparent algorithm. Interpretation of the mechanisms of biodegradation was also carried out based on the models developed. © 2014 SETAC.

Multi-Instance Metric Transfer Learning for Genome-Wide Protein Function Prediction.

PubMed

Xu, Yonghui; Min, Huaqing; Wu, Qingyao; Song, Hengjie; Ye, Bicui

2017-02-06

Multi-Instance (MI) learning has been proven to be effective for the genome-wide protein function prediction problems where each training example is associated with multiple instances. Many studies in this literature attempted to find an appropriate Multi-Instance Learning (MIL) method for genome-wide protein function prediction under a usual assumption, the underlying distribution from testing data (target domain, i.e., TD) is the same as that from training data (source domain, i.e., SD). However, this assumption may be violated in real practice. To tackle this problem, in this paper, we propose a Multi-Instance Metric Transfer Learning (MIMTL) approach for genome-wide protein function prediction. In MIMTL, we first transfer the source domain distribution to the target domain distribution by utilizing the bag weights. Then, we construct a distance metric learning method with the reweighted bags. At last, we develop an alternative optimization scheme for MIMTL. Comprehensive experimental evidence on seven real-world organisms verifies the effectiveness and efficiency of the proposed MIMTL approach over several state-of-the-art methods.

A traveling salesman approach for predicting protein functions.

PubMed

Johnson, Olin; Liu, Jing

2006-10-12

Protein-protein interaction information can be used to predict unknown protein functions and to help study biological pathways. Here we present a new approach utilizing the classic Traveling Salesman Problem to study the protein-protein interactions and to predict protein functions in budding yeast Saccharomyces cerevisiae. We apply the global optimization tool from combinatorial optimization algorithms to cluster the yeast proteins based on the global protein interaction information. We then use this clustering information to help us predict protein functions. We use our algorithm together with the direct neighbor algorithm 1 on characterized proteins and compare the prediction accuracy of the two methods. We show our algorithm can produce better predictions than the direct neighbor algorithm, which only considers the immediate neighbors of the query protein. Our method is a promising one to be used as a general tool to predict functions of uncharacterized proteins and a successful sample of using computer science knowledge and algorithms to study biological problems.

A traveling salesman approach for predicting protein functions

PubMed Central

Johnson, Olin; Liu, Jing

2006-01-01

Background Protein-protein interaction information can be used to predict unknown protein functions and to help study biological pathways. Results Here we present a new approach utilizing the classic Traveling Salesman Problem to study the protein-protein interactions and to predict protein functions in budding yeast Saccharomyces cerevisiae. We apply the global optimization tool from combinatorial optimization algorithms to cluster the yeast proteins based on the global protein interaction information. We then use this clustering information to help us predict protein functions. We use our algorithm together with the direct neighbor algorithm [1] on characterized proteins and compare the prediction accuracy of the two methods. We show our algorithm can produce better predictions than the direct neighbor algorithm, which only considers the immediate neighbors of the query protein. Conclusion Our method is a promising one to be used as a general tool to predict functions of uncharacterized proteins and a successful sample of using computer science knowledge and algorithms to study biological problems. PMID:17147783

Characterization and prediction of residues determining protein functional specificity.

PubMed

Capra, John A; Singh, Mona

2008-07-01

Within a homologous protein family, proteins may be grouped into subtypes that share specific functions that are not common to the entire family. Often, the amino acids present in a small number of sequence positions determine each protein's particular functional specificity. Knowledge of these specificity determining positions (SDPs) aids in protein function prediction, drug design and experimental analysis. A number of sequence-based computational methods have been introduced for identifying SDPs; however, their further development and evaluation have been hindered by the limited number of known experimentally determined SDPs. We combine several bioinformatics resources to automate a process, typically undertaken manually, to build a dataset of SDPs. The resulting large dataset, which consists of SDPs in enzymes, enables us to characterize SDPs in terms of their physicochemical and evolutionary properties. It also facilitates the large-scale evaluation of sequence-based SDP prediction methods. We present a simple sequence-based SDP prediction method, GroupSim, and show that, surprisingly, it is competitive with a representative set of current methods. We also describe ConsWin, a heuristic that considers sequence conservation of neighboring amino acids, and demonstrate that it improves the performance of all methods tested on our large dataset of enzyme SDPs. Datasets and GroupSim code are available online at http://compbio.cs.princeton.edu/specificity/. Supplementary data are available at Bioinformatics online.

Predictive computation of genomic logic processing functions in embryonic development

PubMed Central

Peter, Isabelle S.; Faure, Emmanuel; Davidson, Eric H.

2012-01-01

Gene regulatory networks (GRNs) control the dynamic spatial patterns of regulatory gene expression in development. Thus, in principle, GRN models may provide system-level, causal explanations of developmental process. To test this assertion, we have transformed a relatively well-established GRN model into a predictive, dynamic Boolean computational model. This Boolean model computes spatial and temporal gene expression according to the regulatory logic and gene interactions specified in a GRN model for embryonic development in the sea urchin. Additional information input into the model included the progressive embryonic geometry and gene expression kinetics. The resulting model predicted gene expression patterns for a large number of individual regulatory genes each hour up to gastrulation (30 h) in four different spatial domains of the embryo. Direct comparison with experimental observations showed that the model predictively computed these patterns with remarkable spatial and temporal accuracy. In addition, we used this model to carry out in silico perturbations of regulatory functions and of embryonic spatial organization. The model computationally reproduced the altered developmental functions observed experimentally. Two major conclusions are that the starting GRN model contains sufficiently complete regulatory information to permit explanation of a complex developmental process of gene expression solely in terms of genomic regulatory code, and that the Boolean model provides a tool with which to test in silico regulatory circuitry and developmental perturbations. PMID:22927416

The utility of liver function tests for mortality prediction within one year in primary care using the algorithm for liver function investigations (ALFI).

PubMed

McLernon, David J; Dillon, John F; Sullivan, Frank M; Roderick, Paul; Rosenberg, William M; Ryder, Stephen D; Donnan, Peter T

2012-01-01

Although liver function tests (LFTs) are routinely measured in primary care, raised levels in patients with no obvious liver disease may trigger a range of subsequent expensive and unnecessary management plans. The aim of this study was to develop and validate a prediction model to guide decision-making by general practitioners, which estimates risk of one year all-cause mortality in patients with no obvious liver disease. In this population-based historical cohort study, biochemistry data from patients in Tayside, Scotland, with LFTs performed in primary care were record-linked to secondary care and prescription databases to ascertain baseline characteristics, and to mortality data. Using this derivation cohort a survival model was developed to predict mortality. The model was assessed for calibration, discrimination (using the C-statistic) and performance, and validated using a separate cohort of Scottish primary care practices. From the derivation cohort (n = 95 977), 2.7% died within one year. Predictors of mortality included: age; male gender; social deprivation; history of cancer, renal disease, stroke, ischaemic heart disease or respiratory disease; statin use; and LFTs (albumin, transaminase, alkaline phosphatase, bilirubin, and gamma-glutamyltransferase). The C-statistic for the final model was 0.82 (95% CI 0.80-0.84), and was similar in the validation cohort (n = 11 653) 0.86 (0.79-0.90). As an example of performance, for a 10% predicted probability cut-off, sensitivity = 52.8%, specificity = 94.0%, PPV = 21.0%, NPV = 98.5%. For the model without LFTs the respective values were 43.8%, 92.8%, 15.6%, 98.1%. The Algorithm for Liver Function Investigations (ALFI) is the first model to successfully estimate the probability of all-cause mortality in patients with no apparent liver disease having LFTs in primary care. While LFTs added to the model's discrimination and sensitivity, the clinical utility of ALFI remains to be established

An empirical propellant response function for combustion stability predictions

NASA Technical Reports Server (NTRS)

Hessler, R. O.

1980-01-01

An empirical response function model was developed for ammonium perchlorate propellants to supplant T-burner testing at the preliminary design stage. The model was developed by fitting a limited T-burner data base, in terms of oxidizer size and concentration, to an analytical two parameter response function expression. Multiple peaks are predicted, but the primary effect is of a single peak for most formulations, with notable bulges for the various AP size fractions. The model was extended to velocity coupling with the assumption that dynamic response was controlled primarily by the solid phase described by the two parameter model. The magnitude of velocity coupling was then scaled using an erosive burning law. Routine use of the model for stability predictions on a number of propulsion units indicates that the model tends to overpredict propellant response. It is concluded that the model represents a generally conservative prediction tool, suited especially for the preliminary design stage when T-burner data may not be readily available. The model work included development of a rigorous summation technique for pseudopropellant properties and of a concept for modeling ordered packing of particulates.

Predicting Item Difficulty in a Reading Comprehension Test with an Artificial Neural Network.

ERIC Educational Resources Information Center

Perkins, Kyle; And Others

This paper reports the results of using a three-layer backpropagation artificial neural network to predict item difficulty in a reading comprehension test. Two network structures were developed, one with and one without a sigmoid function in the output processing unit. The data set, which consisted of a table of coded test items and corresponding…

Physiological and biochemical basis of clinical liver function tests: a review.

PubMed

Hoekstra, Lisette T; de Graaf, Wilmar; Nibourg, Geert A A; Heger, Michal; Bennink, Roelof J; Stieger, Bruno; van Gulik, Thomas M

2013-01-01

To review the literature on the most clinically relevant and novel liver function tests used for the assessment of hepatic function before liver surgery. Postoperative liver failure is the major cause of mortality and morbidity after partial liver resection and develops as a result of insufficient remnant liver function. Therefore, accurate preoperative assessment of the future remnant liver function is mandatory in the selection of candidates for safe partial liver resection. A MEDLINE search was performed using the key words "liver function tests," "functional studies in the liver," "compromised liver," "physiological basis," and "mechanistic background," with and without Boolean operators. Passive liver function tests, including biochemical parameters and clinical grading systems, are not accurate enough in predicting outcome after liver surgery. Dynamic quantitative liver function tests, such as the indocyanine green test and galactose elimination capacity, are more accurate as they measure the elimination process of a substance that is cleared and/or metabolized almost exclusively by the liver. However, these tests only measure global liver function. Nuclear imaging techniques ((99m)Tc-galactosyl serum albumin scintigraphy and (99m)Tc-mebrofenin hepatobiliary scintigraphy) can measure both total and future remnant liver function and potentially identify patients at risk for postresectional liver failure. Because of the complexity of liver function, one single test does not represent overall liver function. In addition to computed tomography volumetry, quantitative liver function tests should be used to determine whether a safe resection can be performed. Presently, (99m)Tc-mebrofenin hepatobiliary scintigraphy seems to be the most valuable quantitative liver function test, as it can measure multiple aspects of liver function in, specifically, the future remnant liver.

The Trail Making test: a study of its ability to predict falls in the acute neurological in-patient population.

PubMed

Mateen, Bilal Akhter; Bussas, Matthias; Doogan, Catherine; Waller, Denise; Saverino, Alessia; Király, Franz J; Playford, E Diane

2018-05-01

To determine whether tests of cognitive function and patient-reported outcome measures of motor function can be used to create a machine learning-based predictive tool for falls. Prospective cohort study. Tertiary neurological and neurosurgical center. In all, 337 in-patients receiving neurosurgical, neurological, or neurorehabilitation-based care. Binary (Y/N) for falling during the in-patient episode, the Trail Making Test (a measure of attention and executive function) and the Walk-12 (a patient-reported measure of physical function). The principal outcome was a fall during the in-patient stay ( n = 54). The Trail test was identified as the best predictor of falls. Moreover, addition of other variables, did not improve the prediction (Wilcoxon signed-rank P < 0.001). Classical linear statistical modeling methods were then compared with more recent machine learning based strategies, for example, random forests, neural networks, support vector machines. The random forest was the best modeling strategy when utilizing just the Trail Making Test data (Wilcoxon signed-rank P < 0.001) with 68% (± 7.7) sensitivity, and 90% (± 2.3) specificity. This study identifies a simple yet powerful machine learning (Random Forest) based predictive model for an in-patient neurological population, utilizing a single neuropsychological test of cognitive function, the Trail Making test.

Phagonaute: A web-based interface for phage synteny browsing and protein function prediction.

PubMed

Delattre, Hadrien; Souiai, Oussema; Fagoonee, Khema; Guerois, Raphaël; Petit, Marie-Agnès

2016-09-01

Distant homology search tools are of great help to predict viral protein functions. However, due to the lack of profile databases dedicated to viruses, they can lack sensitivity. We constructed HMM profiles for more than 80,000 proteins from both phages and archaeal viruses, and performed all pairwise comparisons with HHsearch program. The whole resulting database can be explored through a user-friendly "Phagonaute" interface to help predict functions. Results are displayed together with their genetic context, to strengthen inferences based on remote homology. Beyond function prediction, this tool permits detections of co-occurrences, often indicative of proteins completing a task together, and observation of conserved patterns across large evolutionary distances. As a test, Herpes simplex virus I was added to Phagonaute, and 25% of its proteome matched to bacterial or archaeal viral protein counterparts. Phagonaute should therefore help virologists in their quest for protein functions and evolutionary relationships. Copyright © 2016 Elsevier Inc. All rights reserved.

The 6-minute walk test in chronic respiratory failure: does observed or predicted walk distance better reflect patient functional status?

PubMed

Güngör, Gökay; Karakurt, Zuhal; Adigüzel, Nalan; Aydin, Rüya Evin; Balci, Merih Kalamanoğlu; Saltürk, Cüneyt; Sancar, Raziye; Solmaz, Suat; Moçin, Özlem Yazicioğlu

2013-05-01

Acquiring 6-min walk test (6MWT) data from patients undergoing noninvasive mechanical ventilation due to chronic hypercapnic respiratory failure is limited. We aimed to assess whether the actual 6-min walk distance (6MWD) or the percent predicted 6MWD is a better reflection of the respiratory function of patients using home noninvasive ventilation (NIV) due to chronic hypercapnic respiratory failure. This was a cross-sectional observational study. The 6MWT was performed in subjects using home NIV. Diagnoses were grouped as COPD, obesity hypoventilation syndrome (OHS), kyphoscoliosis, and parenchymal lung disease. Sex, age, and body mass index (BMI) were used to calculate ideal 6MWD. Male: 1,140 m - (5.61 × BMI) - (6.94 × age), and subtract 153 m for the lower limit of normal. Female: 1,017 m - (6.24 × BMI) - (5.83 × age), and subtract 139 m for the lower limit of normal. The 6MWD and percent-of-predicted 6MWD were compared relative to arterial blood gas, spirometry values, and diagnosis. The 6MWT was performed in 144 subjects, median (IQR) age 62 y (55-71 y). The male/female ratio, median (IQR) 6MWD, and percent-of-predicted 6MWD values were: COPD 32/6, 316 m (226-390 m), and 59.4% (42.5-68.9%); OHS 24/28, 303 m (240-362 m), and 73.0% (63.0-82.0%); kyphoscoliosis 16/7, 420 m (318-462 m), and 70.5% (56.0-75.2%); and parenchymal lung disease 19/12, 333 m (273-372 m), and 67.1% (46.7-74.7%). The correlation of percent-of-predicted 6MWD with spirometry and arterial blood gas values were better than with the actual 6MWD. The percent-of-predicted 6MWD was better correlated with respiratory function than actual 6MWD for subjects using home NIV due to chronic hypercapnic respiratory failure with COPD, OHS, kyphoscoliosis, and parenchymal lung disease.

Test-Anchored Vibration Response Predictions for an Acoustically Energized Curved Orthogrid Panel with Mounted Components

NASA Technical Reports Server (NTRS)

Frady, Gregory P.; Duvall, Lowery D.; Fulcher, Clay W. G.; Laverde, Bruce T.; Hunt, Ronald A.

2011-01-01

rich body of vibroacoustic test data was recently generated at Marshall Space Flight Center for component-loaded curved orthogrid panels typical of launch vehicle skin structures. The test data were used to anchor computational predictions of a variety of spatially distributed responses including acceleration, strain and component interface force. Transfer functions relating the responses to the input pressure field were generated from finite element based modal solutions and test-derived damping estimates. A diffuse acoustic field model was applied to correlate the measured input sound pressures across the energized panel. This application quantifies the ability to quickly and accurately predict a variety of responses to acoustically energized skin panels with mounted components. Favorable comparisons between the measured and predicted responses were established. The validated models were used to examine vibration response sensitivities to relevant modeling parameters such as pressure patch density, mesh density, weight of the mounted component and model form. Convergence metrics include spectral densities and cumulative root-mean squared (RMS) functions for acceleration, velocity, displacement, strain and interface force. Minimum frequencies for response convergence were established as well as recommendations for modeling techniques, particularly in the early stages of a component design when accurate structural vibration requirements are needed relatively quickly. The results were compared with long-established guidelines for modeling accuracy of component-loaded panels. A theoretical basis for the Response/Pressure Transfer Function (RPTF) approach provides insight into trends observed in the response predictions and confirmed in the test data. The software developed for the RPTF method allows easy replacement of the diffuse acoustic field with other pressure fields such as a turbulent boundary layer (TBL) model suitable for vehicle ascent. Structural responses

Functional Performance Testing After Anterior Cruciate Ligament Reconstruction

PubMed Central

Abrams, Geoffrey D.; Harris, Joshua D.; Gupta, Anil K.; McCormick, Frank M.; Bush-Joseph, Charles A.; Verma, Nikhil N.; Cole, Brian J.; Bach, Bernard R.

2014-01-01

testing was the most commonly reported functional test following ACL reconstruction. Increases in performance on functional tests were predictably seen as time increased following surgery. Those with hamstring autografts may experience increased strength deficits with knee flexion versus those having BPTB autograft. These data provide information that may assist providers in determining timing of return to unrestricted sporting activity. PMID:26535266

Benchmarking the Performance of Exchange-Correlation Functionals for Predicting Two-Photon Absorption Strengths.

PubMed

Beerepoot, Maarten T P; Alam, Md Mehboob; Bednarska, Joanna; Bartkowiak, Wojciech; Ruud, Kenneth; Zaleśny, Robert

2018-06-15

The present work investigates the performance of exchange-correlation functionals in the prediction of two-photon absorption (2PA) strengths. For this purpose, we considered six common functionals used for studying 2PA processes and tested these on six organoboron chelates. The set consisted of two semilocal (PBE and BLYP), two hybrid (B3LYP and PBE0), and two range-separated (LC-BLYP and CAM-B3LYP) functionals. The RI-CC2 method was chosen as a reference level and was found to give results consistent with the experimental data that are available for three of the molecules considered. Of the six exchange-correlation functionals studied, only the range-separated functionals predict an ordering of the 2PA strengths that is consistent with experimental and RI-CC2 results. Even though the range-separated functionals predict correct relative trends, the absolute values for the 2PA strengths are underestimated by a factor of 2-6 for the molecules considered. An in-depth analysis, on the basis of the derived generalized few-state model expression for the 2PA strength for a coupled-cluster wave function, reveals that the problem with these functionals can be linked to underestimated excited-state dipole moments and, to a lesser extent, overestimated excitation energies. The semilocal and hybrid functionals exhibit less predictable errors and a variation in the 2PA strengths in disagreement with the reference results. The semilocal and hybrid functionals show smaller average errors than the range-separated functionals, but our analysis reveals that this is due to fortuitous error cancellation between excitation energies and the transition dipole moments. Our results constitute a warning against using currently available exchange-correlation functionals in the prediction of 2PA strengths and highlight the need for functionals that correctly describe the electron density of excited electronic states.

The function and failure of sensory predictions.

PubMed

Bansal, Sonia; Ford, Judith M; Spering, Miriam

2018-04-23

Humans and other primates are equipped with neural mechanisms that allow them to automatically make predictions about future events, facilitating processing of expected sensations and actions. Prediction-driven control and monitoring of perceptual and motor acts are vital to normal cognitive functioning. This review provides an overview of corollary discharge mechanisms involved in predictions across sensory modalities and discusses consequences of predictive coding for cognition and behavior. Converging evidence now links impairments in corollary discharge mechanisms to neuropsychiatric symptoms such as hallucinations and delusions. We review studies supporting a prediction-failure hypothesis of perceptual and cognitive disturbances. We also outline neural correlates underlying prediction function and failure, highlighting similarities across the visual, auditory, and somatosensory systems. In linking basic psychophysical and psychophysiological evidence of visual, auditory, and somatosensory prediction failures to neuropsychiatric symptoms, our review furthers our understanding of disease mechanisms. © 2018 New York Academy of Sciences.

PredictProtein—an open resource for online prediction of protein structural and functional features

PubMed Central

Yachdav, Guy; Kloppmann, Edda; Kajan, Laszlo; Hecht, Maximilian; Goldberg, Tatyana; Hamp, Tobias; Hönigschmid, Peter; Schafferhans, Andrea; Roos, Manfred; Bernhofer, Michael; Richter, Lothar; Ashkenazy, Haim; Punta, Marco; Schlessinger, Avner; Bromberg, Yana; Schneider, Reinhard; Vriend, Gerrit; Sander, Chris; Ben-Tal, Nir; Rost, Burkhard

2014-01-01

PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of structure (secondary structure, solvent accessibility, transmembrane helices (TMSEG) and strands, coiled-coil regions, disulfide bonds and disordered regions) and function. The service incorporates analysis methods for the identification of functional regions (ConSurf), homology-based inference of Gene Ontology terms (metastudent), comprehensive subcellular localization prediction (LocTree3), protein–protein binding sites (ISIS2), protein–polynucleotide binding sites (SomeNA) and predictions of the effect of point mutations (non-synonymous SNPs) on protein function (SNAP2). Our goal has always been to develop a system optimized to meet the demands of experimentalists not highly experienced in bioinformatics. To this end, the PredictProtein results are presented as both text and a series of intuitive, interactive and visually appealing figures. The web server and sources are available at http://ppopen.rostlab.org. PMID:24799431

Connectome-based predictive modeling of attention: Comparing different functional connectivity features and prediction methods across datasets.

PubMed

Yoo, Kwangsun; Rosenberg, Monica D; Hsu, Wei-Ting; Zhang, Sheng; Li, Chiang-Shan R; Scheinost, Dustin; Constable, R Todd; Chun, Marvin M

2018-02-15

Connectome-based predictive modeling (CPM; Finn et al., 2015; Shen et al., 2017) was recently developed to predict individual differences in traits and behaviors, including fluid intelligence (Finn et al., 2015) and sustained attention (Rosenberg et al., 2016a), from functional brain connectivity (FC) measured with fMRI. Here, using the CPM framework, we compared the predictive power of three different measures of FC (Pearson's correlation, accordance, and discordance) and two different prediction algorithms (linear and partial least square [PLS] regression) for attention function. Accordance and discordance are recently proposed FC measures that respectively track in-phase synchronization and out-of-phase anti-correlation (Meskaldji et al., 2015). We defined connectome-based models using task-based or resting-state FC data, and tested the effects of (1) functional connectivity measure and (2) feature-selection/prediction algorithm on individualized attention predictions. Models were internally validated in a training dataset using leave-one-subject-out cross-validation, and externally validated with three independent datasets. The training dataset included fMRI data collected while participants performed a sustained attention task and rested (N = 25; Rosenberg et al., 2016a). The validation datasets included: 1) data collected during performance of a stop-signal task and at rest (N = 83, including 19 participants who were administered methylphenidate prior to scanning; Farr et al., 2014a; Rosenberg et al., 2016b), 2) data collected during Attention Network Task performance and rest (N = 41, Rosenberg et al., in press), and 3) resting-state data and ADHD symptom severity from the ADHD-200 Consortium (N = 113; Rosenberg et al., 2016a). Models defined using all combinations of functional connectivity measure (Pearson's correlation, accordance, and discordance) and prediction algorithm (linear and PLS regression) predicted attentional abilities, with

Physical Function Does Not Predict Care Assessment Need Score in Older Veterans.

PubMed

Serra, Monica C; Addison, Odessa; Giffuni, Jamie; Paden, Lydia; Morey, Miriam C; Katzel, Leslie

2017-01-01

The Veterans Health Administration's Care Assessment Need (CAN) score is a statistical model, aimed to predict high-risk patients. We were interested in determining if a relationship existed between physical function and CAN scores. Seventy-four older (71 ± 1 years) male Veterans underwent assessment of CAN score and subjective (Short Form-36 [SF-36]) and objective (self-selected walking speed, four square step test, short physical performance battery) assessment of physical function. Approximately 25% of participants self-reported limitations performing lower intensity activities, while 70% to 90% reported limitations with more strenuous activities. When compared with cut points indicative of functional limitations, 35% to 65% of participants had limitations for each of the objective measures. Any measure of subjective or objective physical function did not predict CAN score. These data indicate that the addition of a physical function assessment may complement the CAN score in the identification of high-risk patients.

Roles for text mining in protein function prediction.

PubMed

Verspoor, Karin M

2014-01-01

The Human Genome Project has provided science with a hugely valuable resource: the blueprints for life; the specification of all of the genes that make up a human. While the genes have all been identified and deciphered, it is proteins that are the workhorses of the human body: they are essential to virtually all cell functions and are the primary mechanism through which biological function is carried out. Hence in order to fully understand what happens at a molecular level in biological organisms, and eventually to enable development of treatments for diseases where some aspect of a biological system goes awry, we must understand the functions of proteins. However, experimental characterization of protein function cannot scale to the vast amount of DNA sequence data now available. Computational protein function prediction has therefore emerged as a problem at the forefront of modern biology (Radivojac et al., Nat Methods 10(13):221-227, 2013).Within the varied approaches to computational protein function prediction that have been explored, there are several that make use of biomedical literature mining. These methods take advantage of information in the published literature to associate specific proteins with specific protein functions. In this chapter, we introduce two main strategies for doing this: association of function terms, represented as Gene Ontology terms (Ashburner et al., Nat Genet 25(1):25-29, 2000), to proteins based on information in published articles, and a paradigm called LEAP-FS (Literature-Enhanced Automated Prediction of Functional Sites) in which literature mining is used to validate the predictions of an orthogonal computational protein function prediction method.

Test-Anchored Vibration Response Predictions for an Acoustically Energized Curved Orthogrid Panel with Mounted Components

NASA Technical Reports Server (NTRS)

Frady, Gregory P.; Duvall, Lowery D.; Fulcher, Clay W. G.; Laverde, Bruce T.; Hunt, Ronald A.

2011-01-01

A rich body of vibroacoustic test data was recently generated at Marshall Space Flight Center for a curved orthogrid panel typical of launch vehicle skin structures. Several test article configurations were produced by adding component equipment of differing weights to the flight-like vehicle panel. The test data were used to anchor computational predictions of a variety of spatially distributed responses including acceleration, strain and component interface force. Transfer functions relating the responses to the input pressure field were generated from finite element based modal solutions and test-derived damping estimates. A diffuse acoustic field model was employed to describe the assumed correlation of phased input sound pressures across the energized panel. This application demonstrates the ability to quickly and accurately predict a variety of responses to acoustically energized skin panels with mounted components. Favorable comparisons between the measured and predicted responses were established. The validated models were used to examine vibration response sensitivities to relevant modeling parameters such as pressure patch density, mesh density, weight of the mounted component and model form. Convergence metrics include spectral densities and cumulative root-mean squared (RMS) functions for acceleration, velocity, displacement, strain and interface force. Minimum frequencies for response convergence were established as well as recommendations for modeling techniques, particularly in the early stages of a component design when accurate structural vibration requirements are needed relatively quickly. The results were compared with long-established guidelines for modeling accuracy of component-loaded panels. A theoretical basis for the Response/Pressure Transfer Function (RPTF) approach provides insight into trends observed in the response predictions and confirmed in the test data. The software modules developed for the RPTF method can be easily adapted for

22 Years of predictive testing for Huntington's disease: the experience of the UK Huntington's Prediction Consortium.

PubMed

Baig, Sheharyar S; Strong, Mark; Rosser, Elisabeth; Taverner, Nicola V; Glew, Ruth; Miedzybrodzka, Zosia; Clarke, Angus; Craufurd, David; Quarrell, Oliver W

2016-10-01

Huntington's disease (HD) is a progressive neurodegenerative condition. At-risk individuals have accessed predictive testing via direct mutation testing since 1993. The UK Huntington's Prediction Consortium has collected anonymised data on UK predictive tests, annually, from 1993 to 2014: 9407 predictive tests were performed across 23 UK centres. Where gender was recorded, 4077 participants were male (44.3%) and 5122 were female (55.7%). The median age of participants was 37 years. The most common reason for predictive testing was to reduce uncertainty (70.5%). Of the 8441 predictive tests on individuals at 50% prior risk, 4629 (54.8%) were reported as mutation negative and 3790 (44.9%) were mutation positive, with 22 (0.3%) in the database being uninterpretable. Using a prevalence figure of 12.3 × 10(-5), the cumulative uptake of predictive testing in the 50% at-risk UK population from 1994 to 2014 was estimated at 17.4% (95% CI: 16.9-18.0%). We present the largest study conducted on predictive testing in HD. Our findings indicate that the vast majority of individuals at risk of HD (>80%) have not undergone predictive testing. Future therapies in HD will likely target presymptomatic individuals; therefore, identifying the at-risk population whose gene status is unknown is of significant public health value.

22 Years of predictive testing for Huntington's disease: the experience of the UK Huntington's Prediction Consortium

PubMed Central

Baig, Sheharyar S; Strong, Mark; Rosser, Elisabeth; Taverner, Nicola V; Glew, Ruth; Miedzybrodzka, Zosia; Clarke, Angus; Craufurd, David; Quarrell, Oliver W

2016-01-01

Huntington's disease (HD) is a progressive neurodegenerative condition. At-risk individuals have accessed predictive testing via direct mutation testing since 1993. The UK Huntington's Prediction Consortium has collected anonymised data on UK predictive tests, annually, from 1993 to 2014: 9407 predictive tests were performed across 23 UK centres. Where gender was recorded, 4077 participants were male (44.3%) and 5122 were female (55.7%). The median age of participants was 37 years. The most common reason for predictive testing was to reduce uncertainty (70.5%). Of the 8441 predictive tests on individuals at 50% prior risk, 4629 (54.8%) were reported as mutation negative and 3790 (44.9%) were mutation positive, with 22 (0.3%) in the database being uninterpretable. Using a prevalence figure of 12.3 × 10−5, the cumulative uptake of predictive testing in the 50% at-risk UK population from 1994 to 2014 was estimated at 17.4% (95% CI: 16.9–18.0%). We present the largest study conducted on predictive testing in HD. Our findings indicate that the vast majority of individuals at risk of HD (>80%) have not undergone predictive testing. Future therapies in HD will likely target presymptomatic individuals; therefore, identifying the at-risk population whose gene status is unknown is of significant public health value. PMID:27165004

Year 2 Report: Protein Function Prediction Platform

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

Zhou, C E

2012-04-27

Upon completion of our second year of development in a 3-year development cycle, we have completed a prototype protein structure-function annotation and function prediction system: Protein Function Prediction (PFP) platform (v.0.5). We have met our milestones for Years 1 and 2 and are positioned to continue development in completion of our original statement of work, or a reasonable modification thereof, in service to DTRA Programs involved in diagnostics and medical countermeasures research and development. The PFP platform is a multi-scale computational modeling system for protein structure-function annotation and function prediction. As of this writing, PFP is the only existing fullymore » automated, high-throughput, multi-scale modeling, whole-proteome annotation platform, and represents a significant advance in the field of genome annotation (Fig. 1). PFP modules perform protein functional annotations at the sequence, systems biology, protein structure, and atomistic levels of biological complexity (Fig. 2). Because these approaches provide orthogonal means of characterizing proteins and suggesting protein function, PFP processing maximizes the protein functional information that can currently be gained by computational means. Comprehensive annotation of pathogen genomes is essential for bio-defense applications in pathogen characterization, threat assessment, and medical countermeasure design and development in that it can short-cut the time and effort required to select and characterize protein biomarkers.« less

Non-invasive pulmonary function test on Morquio Patients

PubMed Central

Kubaski, Francyne; Tomatsu, Shunji; Patel, Pravin; Shimada, Tsutomu; Xie, Li; Yasuda, Eriko; Mason, Robert; Mackenzie, William G.; Theroux, Mary; Bober, Michael B.; Oldham, Helen M.; Orii, Tadao; Shaffer, Thomas H.

2015-01-01

In clinical practice, respiratory function tests are difficult to perform in Morquio syndrome patients due to their characteristic skeletal dysplasia, small body size and lack of cooperation of young patients, where in some cases, conventional spirometry for pulmonary function is too challenging. To establish feasible clinical pulmonary endpoints and determine whether age impacts lung function in Morquio patients non-invasive pulmonary tests and conventional spirometry were evaluated. The non-invasive pulmonary tests: impulse oscillometry system, pneumotachography, and respiratory inductance plethysmography in conjunction with conventional spirometry were evaluated in twenty-two Morquio patients (18 Morquio A and 4 Morquio B) (7 males), ranging from 3 and 40 years of age. Twenty-two patients were compliant with non-invasive tests (100%) with exception of IOS (81.8%–18 patients). Seventeen patients (77.3%) were compliant with spirometry testing. All subjects had normal vital signs at rest including > 95% oxygen saturation, end tidal CO2 (38–44 mmHg), and age-appropriate heart rate (mean=98.3, standard deviation=19) (two patients were deviated). All patients preserved normal values in impulse oscillometry system, pneumotachography, and respiratory inductance plethysmography, although predicted forced expiratory volume total (72.8 ± 6.9 SE%) decreased with age and was below normal; phase angle (35.5 ± 16.5 Degrees), %Rib Cage (41.6 ± 12.7%), resonant frequency, and forced expiratory volume in one second/forced expiratory volume total (110.0 ± 3.2 SE%) were normal and not significantly impacted by age. The proposed non-invasive pulmonary function tests are able to cover a greater number of patients (young patients and/or wheel-chair bound), thus providing a new diagnostic approach for the assessment of lung function in Morquio syndrome which in many cases may be difficult to evaluate. Morquio patients studied herein demonstrated no clinical or functional signs

Executive functioning performance predicts subjective and physiological acute stress reactivity: preliminary results.

PubMed

Hendrawan, Donny; Yamakawa, Kaori; Kimura, Motohiro; Murakami, Hiroki; Ohira, Hideki

2012-06-01

Individual differences in baseline executive functioning (EF) capacities have been shown to predict state anxiety during acute stressor exposure. However, no previous studies have clearly demonstrated the relationship between EF and physiological measures of stress. The present study investigated the efficacy of several well-known EF tests (letter fluency, Stroop test, and Wisconsin Card Sorting Test) in predicting both subjective and physiological stress reactivity during acute psychosocial stress exposure. Our results show that letter fluency served as the best predictor for both types of reactivity. Specifically, the higher the letter fluency score, the lower the acute stress reactivity after controlling for the baseline stress response, as indicated by lower levels of state anxiety, negative mood, salivary cortisol, and skin conductance. Moreover, the predictive power of the letter fluency test remained significant for state anxiety and cortisol indices even after further adjustments for covariates by adding the body mass index (BMI) as a covariate. Thus, good EF performance, as reflected by high letter fluency scores, may dampen acute stress responses, which suggests that EF processes are directly associated with aspects of stress regulation. Copyright © 2012 Elsevier B.V. All rights reserved.

Neuropsychological tests for predicting cognitive decline in older adults

PubMed Central

Baerresen, Kimberly M; Miller, Karen J; Hanson, Eric R; Miller, Justin S; Dye, Richelin V; Hartman, Richard E; Vermeersch, David; Small, Gary W

2015-01-01

Summary Aim To determine neuropsychological tests likely to predict cognitive decline. Methods A sample of nonconverters (n = 106) was compared with those who declined in cognitive status (n = 24). Significant univariate logistic regression prediction models were used to create multivariate logistic regression models to predict decline based on initial neuropsychological testing. Results Rey–Osterrieth Complex Figure Test (RCFT) Retention predicted conversion to mild cognitive impairment (MCI) while baseline Buschke Delay predicted conversion to Alzheimer’s disease (AD). Due to group sample size differences, additional analyses were conducted using a subsample of demographically matched nonconverters. Analyses indicated RCFT Retention predicted conversion to MCI and AD, and Buschke Delay predicted conversion to AD. Conclusion Results suggest RCFT Retention and Buschke Delay may be useful in predicting cognitive decline. PMID:26107318

Cost-Sensitive Radial Basis Function Neural Network Classifier for Software Defect Prediction

PubMed Central

Venkatesan, R.

2016-01-01

Effective prediction of software modules, those that are prone to defects, will enable software developers to achieve efficient allocation of resources and to concentrate on quality assurance activities. The process of software development life cycle basically includes design, analysis, implementation, testing, and release phases. Generally, software testing is a critical task in the software development process wherein it is to save time and budget by detecting defects at the earliest and deliver a product without defects to the customers. This testing phase should be carefully operated in an effective manner to release a defect-free (bug-free) software product to the customers. In order to improve the software testing process, fault prediction methods identify the software parts that are more noted to be defect-prone. This paper proposes a prediction approach based on conventional radial basis function neural network (RBFNN) and the novel adaptive dimensional biogeography based optimization (ADBBO) model. The developed ADBBO based RBFNN model is tested with five publicly available datasets from the NASA data program repository. The computed results prove the effectiveness of the proposed ADBBO-RBFNN classifier approach with respect to the considered metrics in comparison with that of the early predictors available in the literature for the same datasets. PMID:27738649

Cost-Sensitive Radial Basis Function Neural Network Classifier for Software Defect Prediction.

PubMed

Kumudha, P; Venkatesan, R

Effective prediction of software modules, those that are prone to defects, will enable software developers to achieve efficient allocation of resources and to concentrate on quality assurance activities. The process of software development life cycle basically includes design, analysis, implementation, testing, and release phases. Generally, software testing is a critical task in the software development process wherein it is to save time and budget by detecting defects at the earliest and deliver a product without defects to the customers. This testing phase should be carefully operated in an effective manner to release a defect-free (bug-free) software product to the customers. In order to improve the software testing process, fault prediction methods identify the software parts that are more noted to be defect-prone. This paper proposes a prediction approach based on conventional radial basis function neural network (RBFNN) and the novel adaptive dimensional biogeography based optimization (ADBBO) model. The developed ADBBO based RBFNN model is tested with five publicly available datasets from the NASA data program repository. The computed results prove the effectiveness of the proposed ADBBO-RBFNN classifier approach with respect to the considered metrics in comparison with that of the early predictors available in the literature for the same datasets.

Short Term Single Station GNSS TEC Prediction Using Radial Basis Function Neural Network

NASA Astrophysics Data System (ADS)

Muslim, Buldan; Husin, Asnawi; Efendy, Joni

2018-04-01

TEC prediction models for 24 hours ahead have been developed from JOG2 GPS TEC data during 2016. Eleven month of TEC data were used as a training model of the radial basis function neural network (RBFNN) and 1 month of last data (December 2016) is used for the RBFNN model testing. The RBFNN inputs are the previous 24 hour TEC data and the minimum of Dst index during the previous 24 hours. Outputs of the model are 24 ahead TEC prediction. Comparison of model prediction show that the RBFNN model is able to predict the next 24 hours TEC is more accurate than the TEC GIM model.

Prediction of gas chromatographic retention indices by the use of radial basis function neural networks.

PubMed

Yao, Xiaojun; Zhang, Xiaoyun; Zhang, Ruisheng; Liu, Mancang; Hu, Zhide; Fan, Botao

2002-05-16

A new method for the prediction of retention indices for a diverse set of compounds from their physicochemical parameters has been proposed. The two used input parameters for representing molecular properties are boiling point and molar volume. Models relating relationships between physicochemical parameters and retention indices of compounds are constructed by means of radial basis function neural networks. To get the best prediction results, some strategies are also employed to optimize the topology and learning parameters of the RBFNNs. For the test set, a predictive correlation coefficient R=0.9910 and root mean squared error of 14.1 are obtained. Results show that radial basis function networks can give satisfactory prediction ability and its optimization is less-time consuming and easy to implement.

Testing 40 Predictions from the Transtheoretical Model Again, with Confidence

ERIC Educational Resources Information Center

Velicer, Wayne F.; Brick, Leslie Ann D.; Fava, Joseph L.; Prochaska, James O.

2013-01-01

Testing Theory-based Quantitative Predictions (TTQP) represents an alternative to traditional Null Hypothesis Significance Testing (NHST) procedures and is more appropriate for theory testing. The theory generates explicit effect size predictions and these effect size estimates, with related confidence intervals, are used to test the predictions.…

21 CFR 868.1890 - Predictive pulmonary-function value calculator.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Predictive pulmonary-function value calculator. 868.1890 Section 868.1890 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN... pulmonary-function value calculator. (a) Identification. A predictive pulmonary-function value calculator is...

21 CFR 868.1890 - Predictive pulmonary-function value calculator.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Predictive pulmonary-function value calculator. 868.1890 Section 868.1890 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN... pulmonary-function value calculator. (a) Identification. A predictive pulmonary-function value calculator is...

Liver function testing with nuclear medicine techniques is coming of age.

PubMed

Bennink, Roelof J; Tulchinsky, Mark; de Graaf, Wilmar; Kadry, Zakiyah; van Gulik, Thomas M

2012-03-01

Liver function is a broad term, as the organ participates in a multitude of different physiological and biochemical processes, including metabolic, synthetic, and detoxifying functions. However, it is the function of the hepatocyte that is central to sustaining normal life and dealing with disease states. When the liver begins to fail in severely ill patients, it forecasts a terminal outcome. However, unlike the glomerular filtration rate which clearly quantifies the key renal function, at most practice sites, there is no clinically available quantitative test for liver function. Although it is commonplace to assess indirect evidence of that function (by measuring blood levels of its end products and by-products) and to detect an acute injury (by following rising transaminases), a widely available test that would directly measure hepatocellular function is lacking. This article reviews current knowledge on liver function studies and focuses on those nuclear medicine tests available to study the whole liver and regional liver function. The clinical application driving these tests, prediction of remnant liver function after partial hepatectomy for primary liver malignancy or metastatic disease, is addressed here in detail. The test was recently validated for this specific application and was shown to be better than the current standard of practice (computed tomography volumetry), particularly in patients with hepatic comorbidities like cirrhosis, steatosis, or cholestasis. Furthermore, early assessment of regional liver function increase after preoperative portal vein embolization becomes possible with this technology. The limiting factor to a wider acceptance of this test is based on the lack of clinical software that would allow calculation of liver function parameters. This article provides information that enables a clinical nuclear medicine facility to provide this test using readily available equipment. Furthermore, it addresses emerging clinical applications

Functional identity and diversity of animals predict ecosystem functioning better than species-based indices

PubMed Central

Gagic, Vesna; Bartomeus, Ignasi; Jonsson, Tomas; Taylor, Astrid; Winqvist, Camilla; Fischer, Christina; Slade, Eleanor M.; Steffan-Dewenter, Ingolf; Emmerson, Mark; Potts, Simon G.; Tscharntke, Teja; Weisser, Wolfgang; Bommarco, Riccardo

2015-01-01

Drastic biodiversity declines have raised concerns about the deterioration of ecosystem functions and have motivated much recent research on the relationship between species diversity and ecosystem functioning. A functional trait framework has been proposed to improve the mechanistic understanding of this relationship, but this has rarely been tested for organisms other than plants. We analysed eight datasets, including five animal groups, to examine how well a trait-based approach, compared with a more traditional taxonomic approach, predicts seven ecosystem functions below- and above-ground. Trait-based indices consistently provided greater explanatory power than species richness or abundance. The frequency distributions of single or multiple traits in the community were the best predictors of ecosystem functioning. This implies that the ecosystem functions we investigated were underpinned by the combination of trait identities (i.e. single-trait indices) and trait complementarity (i.e. multi-trait indices) in the communities. Our study provides new insights into the general mechanisms that link biodiversity to ecosystem functioning in natural animal communities and suggests that the observed responses were due to the identity and dominance patterns of the trait composition rather than the number or abundance of species per se. PMID:25567651

Use of clinical movement screening tests to predict injury in sport

PubMed Central

Chimera, Nicole J; Warren, Meghan

2016-01-01

Clinical movement screening tests are gaining popularity as a means to determine injury risk and to implement training programs to prevent sport injury. While these screens are being used readily in the clinical field, it is only recently that some of these have started to gain attention from a research perspective. This limits applicability and poses questions to the validity, and in some cases the reliability, of the clinical movement tests as they relate to injury prediction, intervention, and prevention. This editorial will review the following clinical movement screening tests: Functional Movement Screen™, Star Excursion Balance Test, Y Balance Test, Drop Jump Screening Test, Landing Error Scoring System, and the Tuck Jump Analysis in regards to test administration, reliability, validity, factors that affect test performance, intervention programs, and usefulness for injury prediction. It is important to review the aforementioned factors for each of these clinical screening tests as this may help clinicians interpret the current body of literature. While each of these screening tests were developed by clinicians based on what appears to be clinical practice, this paper brings to light that this is a need for collaboration between clinicians and researchers to ensure validity of clinically meaningful tests so that they are used appropriately in future clinical practice. Further, this editorial may help to identify where the research is lacking and, thus, drive future research questions in regards to applicability and appropriateness of clinical movement screening tools. PMID:27114928

Unified Sequence-Based Association Tests Allowing for Multiple Functional Annotations and Meta-analysis of Noncoding Variation in Metabochip Data.

PubMed

He, Zihuai; Xu, Bin; Lee, Seunggeun; Ionita-Laza, Iuliana

2017-09-07

Substantial progress has been made in the functional annotation of genetic variation in the human genome. Integrative analysis that incorporates such functional annotations into sequencing studies can aid the discovery of disease-associated genetic variants, especially those with unknown function and located outside protein-coding regions. Direct incorporation of one functional annotation as weight in existing dispersion and burden tests can suffer substantial loss of power when the functional annotation is not predictive of the risk status of a variant. Here, we have developed unified tests that can utilize multiple functional annotations simultaneously for integrative association analysis with efficient computational techniques. We show that the proposed tests significantly improve power when variant risk status can be predicted by functional annotations. Importantly, when functional annotations are not predictive of risk status, the proposed tests incur only minimal loss of power in relation to existing dispersion and burden tests, and under certain circumstances they can even have improved power by learning a weight that better approximates the underlying disease model in a data-adaptive manner. The tests can be constructed with summary statistics of existing dispersion and burden tests for sequencing data, therefore allowing meta-analysis of multiple studies without sharing individual-level data. We applied the proposed tests to a meta-analysis of noncoding rare variants in Metabochip data on 12,281 individuals from eight studies for lipid traits. By incorporating the Eigen functional score, we detected significant associations between noncoding rare variants in SLC22A3 and low-density lipoprotein and total cholesterol, associations that are missed by standard dispersion and burden tests. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Confronting species distribution model predictions with species functional traits.

PubMed

Wittmann, Marion E; Barnes, Matthew A; Jerde, Christopher L; Jones, Lisa A; Lodge, David M

2016-02-01

Species distribution models are valuable tools in studies of biogeography, ecology, and climate change and have been used to inform conservation and ecosystem management. However, species distribution models typically incorporate only climatic variables and species presence data. Model development or validation rarely considers functional components of species traits or other types of biological data. We implemented a species distribution model (Maxent) to predict global climate habitat suitability for Grass Carp (Ctenopharyngodon idella). We then tested the relationship between the degree of climate habitat suitability predicted by Maxent and the individual growth rates of both wild (N = 17) and stocked (N = 51) Grass Carp populations using correlation analysis. The Grass Carp Maxent model accurately reflected the global occurrence data (AUC = 0.904). Observations of Grass Carp growth rate covered six continents and ranged from 0.19 to 20.1 g day(-1). Species distribution model predictions were correlated (r = 0.5, 95% CI (0.03, 0.79)) with observed growth rates for wild Grass Carp populations but were not correlated (r = -0.26, 95% CI (-0.5, 0.012)) with stocked populations. Further, a review of the literature indicates that the few studies for other species that have previously assessed the relationship between the degree of predicted climate habitat suitability and species functional traits have also discovered significant relationships. Thus, species distribution models may provide inferences beyond just where a species may occur, providing a useful tool to understand the linkage between species distributions and underlying biological mechanisms.

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

Longitudinal timed function tests in Duchenne muscular dystrophy: ImagingDMD cohort natural history.

PubMed

Arora, Harneet; Willcocks, Rebecca J; Lott, Donovan J; Harrington, Ann T; Senesac, Claudia R; Zilke, Kirsten L; Daniels, Michael J; Xu, Dandan; Tennekoon, Gihan I; Finanger, Erika L; Russman, Barry S; Finkel, Richard S; Triplett, William T; Byrne, Barry J; Walter, Glenn A; Sweeney, H Lee; Vandenborne, Krista

2018-05-09

Tests of ambulatory function are common clinical trial endpoints in Duchenne muscular dystrophy (DMD). The ImagingDMD study has generated a large data set using these tests, which can describe the contemporary natural history of DMD in 5-12.9 year olds. 92 corticosteroid treated boys with DMD and 45 controls participated in this longitudinal study. Subjects performed the 6 minute walk test (6MWT) and timed function tests (TFTs: 10m walk/run, 4 stairs, supine to stand). Boys with DMD had impaired functional performance even at 5-6.9 years. Boys older than 7 had significant declines in function over 1 year for 10m walk/run and 6MWT. 80% of subjects could perform all functional tests at 9 years old. TFTs appear to be slightly more responsive and predictive of disease progression than 6MWT in 7-12.9 year olds. This study provides insight into the contemporary natural history of key functional endpoints in DMD. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.

Assessing the predictive value of a neuropsychological model on concurrent function in acute stroke recovery and rehabilitation.

PubMed

Leitner, Damian; Miller, Harry; Libben, Maya

2018-06-25

Few studies have examined the relationship between cognition and function for acute stroke inpatients utilizing comprehensive methods. This study aimed to assess the relationship of a neuropsychological model, above and beyond a baseline model, with concurrent functional status across multiple domains in the early weeks of stroke recovery and rehabilitation. Seventy-four acute stroke patients were administered a comprehensive neuropsychological assessment. Functional domains of ability, adjustment, and participation were assessed using the Mayo-Portland Adaptability Inventory - 4 (MPAI-4). Hierarchical linear regression was used to assess a neuropsychological model comprised of cognitive tests scores on domains of executive function, memory, and visuospatial-constructional skills (VSC), after accounting for a baseline model comprised of common demographic and stroke variants used to predict outcome. The neuropsychological model was significantly associated, above and beyond the baseline model, with MPAI-4 Ability, Participation, and Total scores (all p-values < .05). The strength of association varied across functional domains. Analyzing tests of executive function, the Color Trails Test-Part 2 predicted MPAI-4 Participation (β = -.46, p = .001), and Total score (β = -.32, p = .02). Neuropsychological assessment contributes independently to the determination of multiple domains of functional function, above and beyond common medical variants of stroke, in the early weeks of recovery and rehabilitation. Multiple tests of executive function are recommended to develop a greater appreciation of a patient's concurrent functional abilities.

Predictive Cutoff Values of the Five-Times Sit-to-Stand Test and the Timed "Up & Go" Test for Disability Incidence in Older People Dwelling in the Community.

PubMed

Makizako, Hyuma; Shimada, Hiroyuki; Doi, Takehiko; Tsutsumimoto, Kota; Nakakubo, Sho; Hotta, Ryo; Suzuki, Takao

2017-04-01

Lower extremity functioning is important for maintaining activity in elderly people. Optimal cutoff points for standard measurements of lower extremity functioning would help identify elderly people who are not disabled but have a high risk of developing disability. The purposes of this study were: (1) to determine the optimal cutoff points of the Five-Times Sit-to-Stand Test and the Timed "Up & Go" Test for predicting the development of disability and (2) to examine the impact of poor performance on both tests on the prediction of the risk of disability in elderly people dwelling in the community. This was a prospective cohort study. A population of 4,335 elderly people dwelling in the community (mean age = 71.7 years; 51.6% women) participated in baseline assessments. Participants were monitored for 2 years for the development of disability. During the 2-year follow-up period, 161 participants (3.7%) developed disability. The optimal cutoff points of the Five-Times Sit-to-Stand Test and the Timed "Up & Go" Test for predicting the development of disability were greater than or equal to 10 seconds and greater than or equal to 9 seconds, respectively. Participants with poor performance on the Five-Times Sit-to-Stand Test (hazard ratio = 1.88; 95% CI = 1.11-3.20), the Timed "Up & Go" Test (hazard ratio = 2.24; 95% CI = 1.42-3.53), or both tests (hazard ratio = 2.78; 95% CI = 1.78-4.33) at the baseline assessment had a significantly higher risk of developing disability than participants who had better lower extremity functioning. All participants had good initial functioning and participated in assessments on their own. Causes of disability were not assessed. Assessments of lower extremity functioning with the Five-Times Sit-to-Stand Test and the Timed "Up & Go" Test, especially poor performance on both tests, were good predictors of future disability in elderly people dwelling in the community. © 2017 American Physical Therapy Association

Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

DOE PAGES

Petters, M. D.; Kreidenweis, S. M.; Ziemann, P. J.

2016-01-19

A wealth of recent laboratory and field experiments demonstrate that organic aerosol composition evolves with time in the atmosphere, leading to changes in the influence of the organic fraction to cloud condensation nuclei (CCN) spectra. There is a need for tools that can realistically represent the evolution of CCN activity to better predict indirect effects of organic aerosol on clouds and climate. This work describes a model to predict the CCN activity of organic compounds from functional group composition. Following previous methods in the literature, we test the ability of semi-empirical group contribution methods in Kohler theory to predict themore » effective hygroscopicity parameter, kappa. However, in our approach we also account for liquid–liquid phase boundaries to simulate phase-limited activation behavior. Model evaluation against a selected database of published laboratory measurements demonstrates that kappa can be predicted within a factor of 2. Simulation of homologous series is used to identify the relative effectiveness of different functional groups in increasing the CCN activity of weakly functionalized organic compounds. Hydroxyl, carboxyl, aldehyde, hydroperoxide, carbonyl, and ether moieties promote CCN activity while methylene and nitrate moieties inhibit CCN activity. Furthermore, the model can be incorporated into scale-bridging test beds such as the Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) to evaluate the evolution of kappa for a complex mix of organic compounds and to develop suitable parameterizations of CCN evolution for larger-scale models.« less

Quantifying confidence in density functional theory predictions of magnetic ground states

NASA Astrophysics Data System (ADS)

Houchins, Gregory; Viswanathan, Venkatasubramanian

2017-10-01

Density functional theory (DFT) simulations, at the generalized gradient approximation (GGA) level, are being routinely used for material discovery based on high-throughput descriptor-based searches. The success of descriptor-based material design relies on eliminating bad candidates and keeping good candidates for further investigation. While DFT has been widely successfully for the former, oftentimes good candidates are lost due to the uncertainty associated with the DFT-predicted material properties. Uncertainty associated with DFT predictions has gained prominence and has led to the development of exchange correlation functionals that have built-in error estimation capability. In this work, we demonstrate the use of built-in error estimation capabilities within the BEEF-vdW exchange correlation functional for quantifying the uncertainty associated with the magnetic ground state of solids. We demonstrate this approach by calculating the uncertainty estimate for the energy difference between the different magnetic states of solids and compare them against a range of GGA exchange correlation functionals as is done in many first-principles calculations of materials. We show that this estimate reasonably bounds the range of values obtained with the different GGA functionals. The estimate is determined as a postprocessing step and thus provides a computationally robust and systematic approach to estimating uncertainty associated with predictions of magnetic ground states. We define a confidence value (c-value) that incorporates all calculated magnetic states in order to quantify the concurrence of the prediction at the GGA level and argue that predictions of magnetic ground states from GGA level DFT is incomplete without an accompanying c-value. We demonstrate the utility of this method using a case study of Li-ion and Na-ion cathode materials and the c-value metric correctly identifies that GGA-level DFT will have low predictability for NaFePO4F . Further, there

Protein Structure and Function Prediction Using I-TASSER

PubMed Central

Yang, Jianyi; Zhang, Yang

2016-01-01

I-TASSER is a hierarchical protocol for automated protein structure prediction and structure-based function annotation. Starting from the amino acid sequence of target proteins, I-TASSER first generates full-length atomic structural models from multiple threading alignments and iterative structural assembly simulations followed by atomic-level structure refinement. The biological functions of the protein, including ligand-binding sites, enzyme commission number, and gene ontology terms, are then inferred from known protein function databases based on sequence and structure profile comparisons. I-TASSER is freely available as both an on-line server and a stand-alone package. This unit describes how to use the I-TASSER protocol to generate structure and function prediction and how to interpret the prediction results, as well as alternative approaches for further improving the I-TASSER modeling quality for distant-homologous and multi-domain protein targets. PMID:26678386

How to test for partially predictable chaos.

PubMed

Wernecke, Hendrik; Sándor, Bulcsú; Gros, Claudius

2017-04-24

For a chaotic system pairs of initially close-by trajectories become eventually fully uncorrelated on the attracting set. This process of decorrelation can split into an initial exponential decrease and a subsequent diffusive process on the chaotic attractor causing the final loss of predictability. Both processes can be either of the same or of very different time scales. In the latter case the two trajectories linger within a finite but small distance (with respect to the overall extent of the attractor) for exceedingly long times and remain partially predictable. Standard tests for chaos widely use inter-orbital correlations as an indicator. However, testing partially predictable chaos yields mostly ambiguous results, as this type of chaos is characterized by attractors of fractally broadened braids. For a resolution we introduce a novel 0-1 indicator for chaos based on the cross-distance scaling of pairs of initially close trajectories. This test robustly discriminates chaos, including partially predictable chaos, from laminar flow. Additionally using the finite time cross-correlation of pairs of initially close trajectories, we are able to identify laminar flow as well as strong and partially predictable chaos in a 0-1 manner solely from the properties of pairs of trajectories.

Functional Task Test (FTT)

NASA Technical Reports Server (NTRS)

Bloomberg, Jacob J.; Mulavara, Ajitkumar; Peters, Brian T.; Rescheke, Millard F.; Wood, Scott; Lawrence, Emily; Koffman, Igor; Ploutz-Snyder, Lori; Spiering, Barry A.; Feeback, Daniel L.;

Calibration and prediction of removal function in magnetorheological finishing.

PubMed

Dai, Yifan; Song, Ci; Peng, Xiaoqiang; Shi, Feng

2010-01-20

A calibrated and predictive model of the removal function has been established based on the analysis of a magnetorheological finishing (MRF) process. By introducing an efficiency coefficient of the removal function, the model can be used to calibrate the removal function in a MRF figuring process and to accurately predict the removal function of a workpiece to be polished whose material is different from the spot part. Its correctness and feasibility have been validated by simulations. Furthermore, applying this model to the MRF figuring experiments, the efficiency coefficient of the removal function can be identified accurately to make the MRF figuring process deterministic and controllable. Therefore, all the results indicate that the calibrated and predictive model of the removal function can improve the finishing determinacy and increase the model applicability in a MRF process.

Efficacy of functional movement screening for predicting injuries in coast guard cadets.

PubMed

Knapik, Joseph J; Cosio-Lima, Ludimila M; Reynolds, Katy L; Shumway, Richard S

2015-05-01

Functional movement screening (FMS) examines the ability of individuals to perform highly specific movements with the aim of identifying individuals who have functional limitations or asymmetries. It is assumed that individuals who can more effectively accomplish the required movements have a lower injury risk. This study determined the ability of FMS to predict injuries in the United States Coast Guard (USCG) cadets. Seven hundred seventy male and 275 female USCG freshman cadets were administered the 7 FMS tests before the physically intense 8-week Summer Warfare Annual Basic (SWAB) training. Physical training-related injuries were recorded during SWAB training. Cumulative injury incidence was calculated at various FMS cutpoint scores. The ability of the FMS total score to predict injuries was examined by calculating sensitivity and specificity. Determination of the FMS cutpoint that maximized specificity and sensitivity was determined from the Youden's index (sensitivity + specificity - 1). For men, FMS scores ≤ 12 were associated with higher injury risk than scores >12; for women, FMS scores ≤ 15 were associated with higher injury risk than scores >15. The Youden's Index indicated that the optimal FMS cutpoint was ≤ 11 for men (22% sensitivity, 87% specificity) and ≤ 14 for women (60% sensitivity, 61% specificity). Functional movement screening demonstrated moderate prognostic accuracy for determining injury risk among female Coast Guard cadets but relatively low accuracy among male cadets. Attempting to predict injury risk based on the FMS test seems to have some limited promise based on the present and past investigations.

Estimation of Reliability Coefficients Using the Test Information Function and Its Modifications.

ERIC Educational Resources Information Center

Samejima, Fumiko

1994-01-01

The reliability coefficient is predicted from the test information function (TIF) or two modified TIF formulas and a specific trait distribution. Examples illustrate the variability of the reliability coefficient across different trait distributions, and results are compared with empirical reliability coefficients. (SLD)

CT volumetry is superior to nuclear renography for prediction of residual kidney function in living donors.

PubMed

Barbas, Andrew S; Li, Yanhong; Zair, Murtuza; Van, Julie A; Famure, Olusegun; Dib, Martin J; Laurence, Jerome M; Kim, S Joseph; Ghanekar, Anand

2016-09-01

Living kidney donor evaluation commonly includes nuclear renography to assess split kidney function and computed tomography (CT) scan to evaluate anatomy. To streamline donor workup and minimize exposure to radioisotopes, we sought to assess the feasibility of using proportional kidney volume from CT volumetry in lieu of nuclear renography. We examined the correlation between techniques and assessed their ability to predict residual postoperative kidney function following live donor nephrectomy. In a cohort of 224 live kidney donors, we compared proportional kidney volume derived by CT volumetry with split kidney function derived from nuclear renography and found only modest correlation (left kidney R(2) =26.2%, right kidney R(2) =26.7%). In a subset of 88 live kidney donors with serum creatinine measured 6 months postoperatively, we compared observed estimated glomerular filtration rate (eGFR) at 6 months with predicted eGFR from preoperative imaging. Compared to nuclear renography, CT volumetry more closely approximated actual observed postoperative eGFR for Chronic Kidney Disease Epidemiology Collaboration (J-test: P=.02, Cox-Pesaran test: P=.01) and Mayo formulas (J-test: P=.004, Cox-Pesaran test: P<.001). These observations support the use of CT volumetry for estimation of split kidney function in healthy individuals with normal kidney function and morphology. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Flight assessment in patients with respiratory disease: hypoxic challenge testing vs. predictive equations.

PubMed

Martin, S E; Bradley, J M; Buick, J B; Bradbury, I; Elborn, J S

2007-06-01

Predictive equations have been proposed as a simpler alternative to hypoxic challenge testing (HCT) for determining the risk of in-flight hypoxia. To assess agreement between hypoxic challenge testing (HCT) and predictive equations for assessment of in-flight hypoxia. Retrospective study. Patients with chronic obstructive pulmonary disease (COPD) (n = 15), interstitial lung disease (ILD) (n = 15) and cystic fibrosis (CF) (n = 15) were studied. Spirometry was recorded prior to hypoxic inhalation and oxygen saturations (SpO2) were recorded before, after and during hypoxic inhalation. Blood gases were analysed before and after hypoxic inhalation and when SpO2 = 85%. An HCT was performed using the Ventimask method. The PaO2 at altitude was estimated for each group using four published predictive equations, which use values of PaO2 (ground) and lung function measurements to predict altitude PaO2. Results were interpreted using the BTS recommendations for prescription of in-flight oxygen post HCT. The Stuart Maxwell test of overall homogeneity was used to assess agreement between HCT results and each of the predictive equations. Ground PaO2 was significantly greater in patients with CF than either ILD or COPD (p < 0.05). PaO2 in all three groups significantly decreased following HCT. With the exception of equation 3, significantly fewer patients in each group would require in-flight O2 if prescription was based on HCT, compared to predictive equations (p < 0.05). Predictive equations considerably overestimate the need for in-flight O2, compared to HCT.

Classical Testing in Functional Linear Models.

PubMed

Kong, Dehan; Staicu, Ana-Maria; Maity, Arnab

2016-01-01

We extend four tests common in classical regression - Wald, score, likelihood ratio and F tests - to functional linear regression, for testing the null hypothesis, that there is no association between a scalar response and a functional covariate. Using functional principal component analysis, we re-express the functional linear model as a standard linear model, where the effect of the functional covariate can be approximated by a finite linear combination of the functional principal component scores. In this setting, we consider application of the four traditional tests. The proposed testing procedures are investigated theoretically for densely observed functional covariates when the number of principal components diverges. Using the theoretical distribution of the tests under the alternative hypothesis, we develop a procedure for sample size calculation in the context of functional linear regression. The four tests are further compared numerically for both densely and sparsely observed noisy functional data in simulation experiments and using two real data applications.

Classical Testing in Functional Linear Models

PubMed Central

Kong, Dehan; Staicu, Ana-Maria; Maity, Arnab

2016-01-01

We extend four tests common in classical regression - Wald, score, likelihood ratio and F tests - to functional linear regression, for testing the null hypothesis, that there is no association between a scalar response and a functional covariate. Using functional principal component analysis, we re-express the functional linear model as a standard linear model, where the effect of the functional covariate can be approximated by a finite linear combination of the functional principal component scores. In this setting, we consider application of the four traditional tests. The proposed testing procedures are investigated theoretically for densely observed functional covariates when the number of principal components diverges. Using the theoretical distribution of the tests under the alternative hypothesis, we develop a procedure for sample size calculation in the context of functional linear regression. The four tests are further compared numerically for both densely and sparsely observed noisy functional data in simulation experiments and using two real data applications. PMID:28955155

Functional brain networks for learning predictive statistics.

PubMed

Giorgio, Joseph; Karlaftis, Vasilis M; Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew; Kourtzi, Zoe

2017-08-18

Making predictions about future events relies on interpreting streams of information that may initially appear incomprehensible. This skill relies on extracting regular patterns in space and time by mere exposure to the environment (i.e., without explicit feedback). Yet, we know little about the functional brain networks that mediate this type of statistical learning. Here, we test whether changes in the processing and connectivity of functional brain networks due to training relate to our ability to learn temporal regularities. By combining behavioral training and functional brain connectivity analysis, we demonstrate that individuals adapt to the environment's statistics as they change over time from simple repetition to probabilistic combinations. Further, we show that individual learning of temporal structures relates to decision strategy. Our fMRI results demonstrate that learning-dependent changes in fMRI activation within and functional connectivity between brain networks relate to individual variability in strategy. In particular, extracting the exact sequence statistics (i.e., matching) relates to changes in brain networks known to be involved in memory and stimulus-response associations, while selecting the most probable outcomes in a given context (i.e., maximizing) relates to changes in frontal and striatal networks. Thus, our findings provide evidence that dissociable brain networks mediate individual ability in learning behaviorally-relevant statistics. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Test-Retest Reliability and Predictive Validity of the Implicit Association Test in Children

ERIC Educational Resources Information Center

Rae, James R.; Olson, Kristina R.

2018-01-01

The Implicit Association Test (IAT) is increasingly used in developmental research despite minimal evidence of whether children's IAT scores are reliable across time or predictive of behavior. When test-retest reliability and predictive validity have been assessed, the results have been mixed, and because these studies have differed on many…

FSPP: A Tool for Genome-Wide Prediction of smORF-Encoded Peptides and Their Functions

PubMed Central

Li, Hui; Xiao, Li; Zhang, Lili; Wu, Jiarui; Wei, Bin; Sun, Ninghui; Zhao, Yi

2018-01-01

smORFs are small open reading frames of less than 100 codons. Recent low throughput experiments showed a lot of smORF-encoded peptides (SEPs) played crucial rule in processes such as regulation of transcription or translation, transportation through membranes and the antimicrobial activity. In order to gather more functional SEPs, it is necessary to have access to genome-wide prediction tools to give profound directions for low throughput experiments. In this study, we put forward a functional smORF-encoded peptides predictor (FSPP) which tended to predict authentic SEPs and their functions in a high throughput method. FSPP used the overlap of detected SEPs from Ribo-seq and mass spectrometry as target objects. With the expression data on transcription and translation levels, FSPP built two co-expression networks. Combing co-location relations, FSPP constructed a compound network and then annotated SEPs with functions of adjacent nodes. Tested on 38 sequenced samples of 5 human cell lines, FSPP successfully predicted 856 out of 960 annotated proteins. Interestingly, FSPP also highlighted 568 functional SEPs from these samples. After comparison, the roles predicted by FSPP were consistent with known functions. These results suggest that FSPP is a reliable tool for the identification of functional small peptides. FSPP source code can be acquired at https://www.bioinfo.org/FSPP. PMID:29675032

Can traits predict individual growth performance? A test in a hyperdiverse tropical forest.

PubMed

Poorter, Lourens; Castilho, Carolina V; Schietti, Juliana; Oliveira, Rafael S; Costa, Flávia R C

2018-07-01

The functional trait approach has, as a central tenet, that plant traits are functional and shape individual performance, but this has rarely been tested in the field. Here, we tested the individual-based trait approach in a hyperdiverse Amazonian tropical rainforest and evaluated intraspecific variation in trait values, plant strategies at the individual level, and whether traits are functional and predict individual performance. We evaluated > 1300 tree saplings belonging to > 383 species, measured 25 traits related to growth and defense, and evaluated the effects of environmental conditions, plant size, and traits on stem growth. A total of 44% of the trait variation was observed within species, indicating a strong potential for acclimation. Individuals showed two strategy spectra, related to tissue toughness and organ size vs leaf display. In this nutrient- and light-limited forest, traits measured at the individual level were surprisingly poor predictors of individual growth performance because of convergence of traits and growth rates. Functional trait approaches based on individuals or species are conceptually fundamentally different: the species-based approach focuses on the potential and the individual-based approach on the realized traits and growth rates. Counterintuitively, the individual approach leads to a poor prediction of individual performance, although it provides a more realistic view on community dynamics. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

COPRED: prediction of fold, GO molecular function and functional residues at the domain level.

PubMed

López, Daniel; Pazos, Florencio

2013-07-15

Only recently the first resources devoted to the functional annotation of proteins at the domain level started to appear. The next step is to develop specific methodologies for predicting function at the domain level based on these resources, and to implement them in web servers to be used by the community. In this work, we present COPRED, a web server for the concomitant prediction of fold, molecular function and functional sites at the domain level, based on a methodology for domain molecular function prediction and a resource of domain functional annotations previously developed and benchmarked. COPRED can be freely accessed at http://csbg.cnb.csic.es/copred. The interface works in all standard web browsers. WebGL (natively supported by most browsers) is required for the in-line preview and manipulation of protein 3D structures. The website includes a detailed help section and usage examples. pazos@cnb.csic.es.

Preoperative EEG predicts memory and selective cognitive functions after temporal lobe surgery.

PubMed Central

Tuunainen, A; Nousiainen, U; Hurskainen, H; Leinonen, E; Pilke, A; Mervaala, E; Vapalahti, M; Partanen, J; Riekkinen, P

1995-01-01

Preoperative and postoperative cognitive and memory functions, psychiatric outcome, and EEGs were evaluated in 32 epileptic patients who underwent temporal lobe surgery. The presence and location of preoperative slow wave focus in routine EEG predicted memory functions of the non-resected side after surgery. Neuropsychological tests of the function of the frontal lobes also showed improvement. Moreover, psychiatric ratings showed that seizure free patients had significantly less affective symptoms postoperatively than those who were still exhibiting seizures. After temporal lobectomies, successful outcome in postoperative memory functions can be achieved in patients with unilateral slow wave activity in preoperative EEGs. This study suggests a new role for routine EEG in preoperative evaluation of patients with temporal lobe epilepsy. PMID:7608663

Predicting multicellular function through multi-layer tissue networks

PubMed Central

Zitnik, Marinka; Leskovec, Jure

2017-01-01

Abstract Motivation: Understanding functions of proteins in specific human tissues is essential for insights into disease diagnostics and therapeutics, yet prediction of tissue-specific cellular function remains a critical challenge for biomedicine. Results: Here, we present OhmNet, a hierarchy-aware unsupervised node feature learning approach for multi-layer networks. We build a multi-layer network, where each layer represents molecular interactions in a different human tissue. OhmNet then automatically learns a mapping of proteins, represented as nodes, to a neural embedding-based low-dimensional space of features. OhmNet encourages sharing of similar features among proteins with similar network neighborhoods and among proteins activated in similar tissues. The algorithm generalizes prior work, which generally ignores relationships between tissues, by modeling tissue organization with a rich multiscale tissue hierarchy. We use OhmNet to study multicellular function in a multi-layer protein interaction network of 107 human tissues. In 48 tissues with known tissue-specific cellular functions, OhmNet provides more accurate predictions of cellular function than alternative approaches, and also generates more accurate hypotheses about tissue-specific protein actions. We show that taking into account the tissue hierarchy leads to improved predictive power. Remarkably, we also demonstrate that it is possible to leverage the tissue hierarchy in order to effectively transfer cellular functions to a functionally uncharacterized tissue. Overall, OhmNet moves from flat networks to multiscale models able to predict a range of phenotypes spanning cellular subsystems. Availability and implementation: Source code and datasets are available at http://snap.stanford.edu/ohmnet. Contact: jure@cs.stanford.edu PMID:28881986

Prediction of functional loss in glaucoma from progressive optic disc damage.

PubMed

Medeiros, Felipe A; Alencar, Luciana M; Zangwill, Linda M; Bowd, Christopher; Sample, Pamela A; Weinreb, Robert N

2009-10-01

To evaluate the ability of progressive optic disc damage detected by assessment of longitudinal stereophotographs to predict future development of functional loss in those with suspected glaucoma. The study included 639 eyes of 407 patients with suspected glaucoma followed up for an average of 8.0 years with annual standard automated perimetry visual field and optic disc stereophotographs. All patients had normal and reliable standard automated perimetry results at baseline. Conversion to glaucoma was defined as development of 3 consecutive abnormal visual fields during follow-up. Presence of progressive optic disc damage was evaluated by grading longitudinally acquired simultaneous stereophotographs. Other predictive factors included age, intraocular pressure, central corneal thickness, pattern standard deviation, and baseline stereophotograph grading. Hazard ratios for predicting visual field loss were obtained by extended Cox models, with optic disc progression as a time-dependent covariate. Predictive accuracy was evaluated using a modified R(2) index. Progressive optic disc damage had a hazard ratio of 25.8 (95% confidence interval, 16.0-41.7) and was the most important risk factor for development of visual field loss with an R(2) of 79%. The R(2)s for other predictive factors ranged from 6% to 26%. Presence of progressive optic disc damage on stereophotographs was a highly predictive factor for future development of functional loss in glaucoma. These findings suggest the importance of careful monitoring of the optic disc appearance and a potential role for longitudinal assessment of the optic disc as an end point in clinical trials and as a reference for evaluation of diagnostic tests in glaucoma.

Functional identity and diversity of animals predict ecosystem functioning better than species-based indices.

PubMed

Gagic, Vesna; Bartomeus, Ignasi; Jonsson, Tomas; Taylor, Astrid; Winqvist, Camilla; Fischer, Christina; Slade, Eleanor M; Steffan-Dewenter, Ingolf; Emmerson, Mark; Potts, Simon G; Tscharntke, Teja; Weisser, Wolfgang; Bommarco, Riccardo

2015-02-22

Drastic biodiversity declines have raised concerns about the deterioration of ecosystem functions and have motivated much recent research on the relationship between species diversity and ecosystem functioning. A functional trait framework has been proposed to improve the mechanistic understanding of this relationship, but this has rarely been tested for organisms other than plants. We analysed eight datasets, including five animal groups, to examine how well a trait-based approach, compared with a more traditional taxonomic approach, predicts seven ecosystem functions below- and above-ground. Trait-based indices consistently provided greater explanatory power than species richness or abundance. The frequency distributions of single or multiple traits in the community were the best predictors of ecosystem functioning. This implies that the ecosystem functions we investigated were underpinned by the combination of trait identities (i.e. single-trait indices) and trait complementarity (i.e. multi-trait indices) in the communities. Our study provides new insights into the general mechanisms that link biodiversity to ecosystem functioning in natural animal communities and suggests that the observed responses were due to the identity and dominance patterns of the trait composition rather than the number or abundance of species per se. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Report on the sixth blind test of organic crystal structure prediction methods

PubMed Central

Reilly, Anthony M.; Cooper, Richard I.; Adjiman, Claire S.; Bhattacharya, Saswata; Boese, A. Daniel; Brandenburg, Jan Gerit; Bygrave, Peter J.; Bylsma, Rita; Campbell, Josh E.; Car, Roberto; Case, David H.; Chadha, Renu; Cole, Jason C.; Cosburn, Katherine; Cuppen, Herma M.; Curtis, Farren; Day, Graeme M.; DiStasio Jr, Robert A.; Dzyabchenko, Alexander; van Eijck, Bouke P.; Elking, Dennis M.; van den Ende, Joost A.; Facelli, Julio C.; Ferraro, Marta B.; Fusti-Molnar, Laszlo; Gatsiou, Christina-Anna; Gee, Thomas S.; de Gelder, René; Ghiringhelli, Luca M.; Goto, Hitoshi; Grimme, Stefan; Guo, Rui; Hofmann, Detlef W. M.; Hoja, Johannes; Hylton, Rebecca K.; Iuzzolino, Luca; Jankiewicz, Wojciech; de Jong, Daniël T.; Kendrick, John; de Klerk, Niek J. J.; Ko, Hsin-Yu; Kuleshova, Liudmila N.; Li, Xiayue; Lohani, Sanjaya; Leusen, Frank J. J.; Lund, Albert M.; Lv, Jian; Ma, Yanming; Marom, Noa; Masunov, Artëm E.; McCabe, Patrick; McMahon, David P.; Meekes, Hugo; Metz, Michael P.; Misquitta, Alston J.; Mohamed, Sharmarke; Monserrat, Bartomeu; Needs, Richard J.; Neumann, Marcus A.; Nyman, Jonas; Obata, Shigeaki; Oberhofer, Harald; Oganov, Artem R.; Orendt, Anita M.; Pagola, Gabriel I.; Pantelides, Constantinos C.; Pickard, Chris J.; Podeszwa, Rafal; Price, Louise S.; Price, Sarah L.; Pulido, Angeles; Read, Murray G.; Reuter, Karsten; Schneider, Elia; Schober, Christoph; Shields, Gregory P.; Singh, Pawanpreet; Sugden, Isaac J.; Szalewicz, Krzysztof; Taylor, Christopher R.; Tkatchenko, Alexandre; Tuckerman, Mark E.; Vacarro, Francesca; Vasileiadis, Manolis; Vazquez-Mayagoitia, Alvaro; Vogt, Leslie; Wang, Yanchao; Watson, Rona E.; de Wijs, Gilles A.; Yang, Jack; Zhu, Qiang; Groom, Colin R.

2016-01-01

The sixth blind test of organic crystal structure prediction (CSP) methods has been held, with five target systems: a small nearly rigid molecule, a polymorphic former drug candidate, a chloride salt hydrate, a co-crystal and a bulky flexible molecule. This blind test has seen substantial growth in the number of participants, with the broad range of prediction methods giving a unique insight into the state of the art in the field. Significant progress has been seen in treating flexible molecules, usage of hierarchical approaches to ranking structures, the application of density-functional approximations, and the establishment of new workflows and ‘best practices’ for performing CSP calculations. All of the targets, apart from a single potentially disordered Z′ = 2 polymorph of the drug candidate, were predicted by at least one submission. Despite many remaining challenges, it is clear that CSP methods are becoming more applicable to a wider range of real systems, including salts, hydrates and larger flexible molecules. The results also highlight the potential for CSP calculations to complement and augment experimental studies of organic solid forms. PMID:27484368

Functional imaging of semantic memory predicts postoperative episodic memory functions in chronic temporal lobe epilepsy.

PubMed

Köylü, Bülent; Walser, Gerald; Ischebeck, Anja; Ortler, Martin; Benke, Thomas

2008-08-05

Medial temporal (MTL) structures have crucial functions in episodic (EM), but also in semantic memory (SM) processing. Preoperative functional magnetic resonance imaging (fMRI) activity within the MTL is increasingly used to predict post-surgical memory capacities. Based on the hypothesis that EM and SM memory functions are both hosted by the MTL the present study wanted to explore the relationship between SM related activations in the MTL as assessed before and the capacity of EM functions after surgery. Patients with chronic unilateral left (n=14) and right (n=12) temporal lobe epilepsy (TLE) performed a standard word list learning test pre- and postoperatively, and a fMRI procedure before the operation using a semantic decision task. SM processing caused significant bilateral MTL activations in both patient groups. While right TLE patients showed asymmetry of fMRI activation with more activation in the left MTL, left TLE patients had almost equal activation in both MTL regions. Contrasting left TLE versus right TLE patients revealed greater activity within the right MTL, whereas no significant difference was observed for the reverse contrast. Greater effect size in the MTL region ipsilateral to the seizure focus was significantly and positively correlated with preoperative EM abilities. Greater effect size in the contralateral MTL was correlated with better postoperative verbal EM, especially in left TLE patients. These results suggest that functional imaging of SM tasks may be useful to predict postoperative verbal memory in TLE. They also advocate a common neuroanatomical basis for SM and EM processes in the MTL.

Modified 30-second Sit to Stand test predicts falls in a cohort of institutionalized older veterans

PubMed Central

Chassé, Kathleen

2017-01-01

Physical function performance tests, including sit to stand tests and Timed Up and Go, assess the functional capacity of older adults. Their ability to predict falls warrants further investigation. The objective was to determine if a modified 30-second Sit to Stand test that allowed upper extremity use and Timed Up and Go test predicted falls in institutionalized Veterans. Fifty-three older adult Veterans (mean age = 91 years, 49 men) residing in a long-term care hospital completed modified 30-second Sit to Stand and Timed Up and Go tests. The number of falls over one year was collected. The ability of modified 30-second Sit to Stand or Timed Up and Go to predict if participants had fallen was examined using logistic regression. The ability of these tests to predict the number of falls was examined using negative binomial regression. Both analyses controlled for age, history of falls, cognition, and comorbidities. The modified 30-second Sit to Stand was significantly (p < 0.05) related to if participants fell (odds ratio = 0.75, 95% confidence interval = 0.58, 0.97) and the number of falls (incidence rate ratio = 0.82, 95% confidence interval = 0.68, 0.98); decreased repetitions were associated with increased number of falls. Timed Up and Go was not significantly (p > 0.05) related to if participants fell (odds ratio = 1.03, 95% confidence interval = 0.96, 1.10) or the number of falls (incidence rate ratio = 1.01, 95% confidence interval = 0.98, 1.05). The modified 30-second Sit to Stand that allowed upper extremity use offers an alternative method to screen for fall risk in older adults in long-term care. PMID:28464024

Modified 30-second Sit to Stand test predicts falls in a cohort of institutionalized older veterans.

PubMed

Applebaum, Eva V; Breton, Dominic; Feng, Zhuo Wei; Ta, An-Tchi; Walsh, Kayley; Chassé, Kathleen; Robbins, Shawn M

2017-01-01

Physical function performance tests, including sit to stand tests and Timed Up and Go, assess the functional capacity of older adults. Their ability to predict falls warrants further investigation. The objective was to determine if a modified 30-second Sit to Stand test that allowed upper extremity use and Timed Up and Go test predicted falls in institutionalized Veterans. Fifty-three older adult Veterans (mean age = 91 years, 49 men) residing in a long-term care hospital completed modified 30-second Sit to Stand and Timed Up and Go tests. The number of falls over one year was collected. The ability of modified 30-second Sit to Stand or Timed Up and Go to predict if participants had fallen was examined using logistic regression. The ability of these tests to predict the number of falls was examined using negative binomial regression. Both analyses controlled for age, history of falls, cognition, and comorbidities. The modified 30-second Sit to Stand was significantly (p < 0.05) related to if participants fell (odds ratio = 0.75, 95% confidence interval = 0.58, 0.97) and the number of falls (incidence rate ratio = 0.82, 95% confidence interval = 0.68, 0.98); decreased repetitions were associated with increased number of falls. Timed Up and Go was not significantly (p > 0.05) related to if participants fell (odds ratio = 1.03, 95% confidence interval = 0.96, 1.10) or the number of falls (incidence rate ratio = 1.01, 95% confidence interval = 0.98, 1.05). The modified 30-second Sit to Stand that allowed upper extremity use offers an alternative method to screen for fall risk in older adults in long-term care.

HPV-testing versus HPV-cytology co-testing to predict the outcome after conization.

PubMed

Bruhn, Laerke Valsøe; Andersen, Sisse Josephine; Hariri, Jalil

2018-06-01

The purpose of this study was to determine the feasibility of human Papillomavirus (HPV) testing alone as a prognostic tool to predict recurrent disease within a three-year follow-up period after treatment for cervical intraepithelial neoplasia (CIN)2 + . Retrospectively, 128 women with histologically verified CIN2 + who had a conization performed at Southern Jutland Hospital in Denmark between 1 January 2013 and 31 December 2013 were included. Histology, cytology and HPV test results were obtained for a three-year follow-up period. 4.7% (6/128) of the cases developed recurrent disease during follow-up. Of the cases without free margins, recurrent dysplasia was detected normal in 10.4% (5/48), whereas in the group with free margins it was 1.3% (1/80). The post-conization HPV test was negative in 67.2% (86/128) and Pap smear normal in 93.7% (120/128). Combining resection margins, cytology and HPV had sensitivity for prediction of recurrent dysplasia of 100%. Specificity was 45.8%, positive predictive value (PPV) 8.5% and negative predictive value (NPV) 100%. Using HPV test alone as a predictor of recurrent dysplasia gave a sensitivity of 83.3%, specificity 69.7%, PPV 11.9% and NPV 98.8%. Combining resection margin and HPV test had a sensitivity of 100%, specificity 45.9%, PPV 8.3% and NPV 100%. HPV test at six months control post-conization gave an NPV of 98.8% and can be used as a solitary test to identify women at risk for recurrent disease three years after treatment for precursor lesions. Using both resection margin and HPV test had a sensitivity of 100% and NPV 100%. Adding cytology did not increase the predictive value. © 2018 Nordic Federation of Societies of Obstetrics and Gynecology.

Prediction of Erectile Function Following Treatment for Prostate Cancer

PubMed Central

Alemozaffar, Mehrdad; Regan, Meredith M.; Cooperberg, Matthew R.; Wei, John T.; Michalski, Jeff M.; Sandler, Howard M.; Hembroff, Larry; Sadetsky, Natalia; Saigal, Christopher S.; Litwin, Mark S.; Klein, Eric; Kibel, Adam S.; Hamstra, Daniel A.; Pisters, Louis L.; Kuban, Deborah A.; Kaplan, Irving D.; Wood, David P.; Ciezki, Jay; Dunn, Rodney L.; Carroll, Peter R.; Sanda, Martin G.

2013-01-01

Context Sexual function is the health-related quality of life (HRQOL) domain most commonly impaired after prostate cancer treatment; however, validated tools to enable personalized prediction of erectile dysfunction after prostate cancer treatment are lacking. Objective To predict long-term erectile function following prostate cancer treatment based on individual patient and treatment characteristics. Design Pretreatment patient characteristics, sexual HRQOL, and treatment details measured in a longitudinal academic multicenter cohort (Prostate Cancer Outcomes and Satisfaction With Treatment Quality Assessment; enrolled from 2003 through 2006), were used to develop models predicting erectile function 2 years after treatment. A community-based cohort (community-based Cancer of the Prostate Strategic Urologic Research Endeavor [CaPSURE]; enrolled 1995 through 2007) externally validated model performance. Patients in US academic and community-based practices whose HRQOL was measured pretreatment (N = 1201) underwent follow-up after prostatectomy, external radiotherapy, or brachytherapy for prostate cancer. Sexual outcomes among men completing 2 years’ follow-up (n = 1027) were used to develop models predicting erectile function that were externally validated among 1913 patients in a community-based cohort. Main Outcome Measures Patient-reported functional erections suitable for intercourse 2 years following prostate cancer treatment. Results Two years after prostate cancer treatment, 368 (37% [95% CI, 34%–40%]) of all patients and 335 (48% [95% CI, 45%–52%]) of those with functional erections prior to treatment reported functional erections; 531 (53% [95% CI, 50%–56%]) of patients without penile prostheses reported use of medications or other devices for erectile dysfunction. Pretreatment sexual HRQOL score, age, serum prostate-specific antigen level, race/ethnicity, body mass index, and intended treatment details were associated with functional erections 2

Predicting rheological behavior and baking quality of wheat flour using a GlutoPeak test.

PubMed

Rakita, Slađana; Dokić, Ljubica; Dapčević Hadnađev, Tamara; Hadnađev, Miroslav; Torbica, Aleksandra

2018-06-01

The purpose of this research was to gain an insight into the ability of the GlutoPeak instrument to predict flour functionality for bread making, as well as to determine which of the GlutoPeak parameters show the best potential in predicting dough rheological behavior and baking performance. Obtained results showed that GlutoPeak parameters correlated better with the indices of extensional rheological tests which consider constant dough hydration than with those which were performed at constant dough consistency. The GlutoPeak test showed that it is suitable for discriminating wheat varieties of good quality from those of poor quality, while the most discriminating index was maximum torque (MT). Moreover, MT value of 50 BU and aggregation energy value of 1,300 GPU were set as limits of wheat flour quality. The backward stepwise regression analysis revealed that a high-level prediction of indices which are highly affected by protein content (gluten content, flour water absorption, and dough tenacity) was achieved by using the GlutoPeak indices. Concerning bread quality, a moderate prediction of specific loaf volume and an intense level prediction of breadcrumb textural properties were accomplished by using the GlutoPeak parameters. The presented results indicated that the application of this quick test in wheat transformation chain for the assessment of baking quality would be useful. Baking test is considered as the most reliable method for assessing wheat-baking quality. However, baking test requires trained stuff, time, and large sample amount. These disadvantages have led to a growing demand to develop new rapid tests which would enable prediction of baked product quality with a limited flour size. Therefore, we tested the possibility of using a GlutoPeak tester to predict loaf volume and breadcrumb textural properties. Discrimination of wheat varieties according to quality with a restricted flour amount was also examined. Furthermore, we proposed the limit

Predicting Changes in Macrophyte Community Structure from Functional Traits in a Freshwater Lake: A Test of Maximum Entropy Model

PubMed Central

Fu, Hui; Zhong, Jiayou; Yuan, Guixiang; Guo, Chunjing; Lou, Qian; Zhang, Wei; Xu, Jun; Ni, Leyi; Xie, Ping; Cao, Te

2015-01-01

Trait-based approaches have been widely applied to investigate how community dynamics respond to environmental gradients. In this study, we applied a series of maximum entropy (maxent) models incorporating functional traits to unravel the processes governing macrophyte community structure along water depth gradient in a freshwater lake. We sampled 42 plots and 1513 individual plants, and measured 16 functional traits and abundance of 17 macrophyte species. Study results showed that maxent model can be highly robust (99.8%) in predicting the species relative abundance of macrophytes with observed community-weighted mean (CWM) traits as the constraints, while relative low (about 30%) with CWM traits fitted from water depth gradient as the constraints. The measured traits showed notably distinct importance in predicting species abundances, with lowest for perennial growth form and highest for leaf dry mass content. For tuber and leaf nitrogen content, there were significant shifts in their effects on species relative abundance from positive in shallow water to negative in deep water. This result suggests that macrophyte species with tuber organ and greater leaf nitrogen content would become more abundant in shallow water, but would become less abundant in deep water. Our study highlights how functional traits distributed across gradients provide a robust path towards predictive community ecology. PMID:26167856

Clinical and electrophysiologic attributes as predictors of results of autonomic function tests

NASA Technical Reports Server (NTRS)

Wu, C. L.; Denq, J. C.; Harper, C. M.; O'Brien, P. C.; Low, P. A.

1998-01-01

Autonomic dysfunction is a feature of some neuropathies and not others. It has been suggested that some clinical and electrophysiologic attributes are predictable of autonomic impairment detected using laboratory testing; however, dear guidelines are unavailable. We evaluated 138 relatively unselected patients with peripheral neuropathy who underwent neurologic evaluation, electromyography (EMG), nerve conduction studies, and autonomic function tests to determine which variables were predictive of laboratory findings of autonomic failure. The variables evaluated were 1) clinical somatic neuropathic findings, 2) clinical autonomic symptoms, and 3) electrophysiologic findings. Autonomic symptoms were strongly predictive (Rs = 0.40, p < 0.001) of autonomic failure. Among the non-autonomic indices, absent ankle reflexes were mildly predictive (Rs = 0.19, p = 0.022) of autonomic impairment, but all others were not (duration, clinical pattern, severity, weakness, sensory loss). Electrophysiologic changes of an axonal neuropathy predicted autonomic impairment while demyelinating neuropathy did not. We conclude that autonomic studies will most likely be abnormal in patients who have symptoms of autonomic involvement and those who have an axonal neuropathy.

Tongue Blade Bite Test Predicts Mandible Fractures

PubMed Central

Neiner, John; Free, Rachael; Caldito, Gloria; Moore-Medlin, Tara; Nathan, Cherie-Ann

2015-01-01

The aim of the study is to evaluate the utility of a simple tongue blade bite test in predicting mandible fractures and use this test as an alternative screening tool for further workup. This is a retrospective chart review. An institutional review board approved the retrospective review of patients evaluated by the Department of Otolaryngology at a single institution for facial trauma performed from November 1, 2011, to February 27, 2014. Patients who had a bite test documented were included in the study. CT was performed in all cases and was used as the gold standard to diagnose mandible fractures. Variables analyzed included age, sex, fracture type/location on CT, bite test positivity, and operative intervention. A total of 86 patients met the inclusion criteria and of those 12 were pediatric patients. Majority of the patients were male (80.2%) and adult (86.0%; average age: 34.3 years). Fifty-seven patients had a negative bite test and on CT scans had no mandible fracture. Twenty-three patients had a positive bite test and a CT scan confirmed fracture. The bite test revealed a sensitivity of 88.5% (95% CI: 69.8–97.6%), specificity of 95.0% (95% CI:86.1–99%), positive predictive value [PPV] of 88.5% (95% CI: 69.8–97.6%), and negative predictive value [NPV] of 95.0% (95% CI: 86.1–99.0%). Among pediatric patients, the sensitivity was 100% (95% CI: 29.9–100%), specificity was 88.9% (95% CI: 68.4–100%), PPV was 75.0% (95% CI: 19.4–99.4%), and NPV was 100% (95% CI: 63.1–100%). The tongue blade bite test is a quick inexpensive diagnostic tool for the otolaryngologist with high sensitivity and specificity for predicting mandible fractures. In the pediatric population, where avoidance of unnecessary CT scans is of highest priority, a wider range of data collection should be undertaken to better assess its utility. PMID:27162567

Cross-Sectional Analysis of the Utility of Pulmonary Function Tests in Predicting Emphysema in Ever-Smokers

PubMed Central

Hesselbacher, Sean E.; Ross, Robert; Schabath, Matthew B.; Smith, E. O’Brian; Perusich, Sarah; Barrow, Nadia; Smithwick, Pamela; Mammen, Manoj J.; Coxson, Harvey; Krowchuk, Natasha; Corry, David B.; Kheradmand, Farrah

2011-01-01

Emphysema is largely an under-diagnosed medical condition that can exist in smokers in the absence of airway obstruction. We aimed to determine the sensitivity and specificity of pulmonary function tests (PFTs) in assessing emphysema using quantitative CT scans as the reference standard. We enrolled 224 ever-smokers (current or former) over the age of 40. CT of thorax was used to quantify the low attenuation area (% emphysema), and to measure the standardized airway wall thickness. PFTs were used individually and in combination to predict their ability to discriminate radiographic emphysema. Significant emphysema (>7%) was detected in 122 (54%) subjects. Twenty six (21%) emphysema subjects had no evidence of airflow obstruction (FEV1/FVC ratio <70%), while all subjects with >23% emphysema showed airflow obstruction. The sensitivity and specificity of spirometry for detecting radiographic emphysema were 79% and 75%, respectively. Standardized airway wall thickness was increased in subjects with airflow obstruction, but did not correlate with emphysema severity. In this cohort of lifetime ever-smokers, PFTs alone were inadequate for diagnosing emphysema. Airway wall thickness quantified by CT morphometry was associated with airflow limitation, but not with emphysema indicating that the heterogeneous nature of lung disease in smokers may represent distinct phenotypes. PMID:21655122

Development and testing of the Test of Functional Health Literacy in Dentistry (TOFHLiD).

PubMed

Gong, Debra A; Lee, Jessica Y; Rozier, R Gary; Pahel, Bhavna T; Richman, Julia A; Vann, William F

2007-01-01

This study aims to evaluate the reliability and validity of the Test of Functional Health Literacy in Dentistry (TOFHLiD), a new instrument to measure functional oral health literacy. TOFHLiD uses text passages and prompts related to fluoride use and access to care to assess reading comprehension and numerical ability. Parents of pediatric dental patients (n = 102) were administered TOFHLiD, a medical literacy comprehension test (TOFHLA), and two word recognition tests [Rapid Estimate of Adult Literacy in Dentistry (REALD), Rapid Estimate of Adult Literacy in Medicine (REALM)]. This design provided assessments of dental and medical health literacy by all subjects, both measured with two different methods (reading/numeracy ability and word recognition). Construct validity of TOFHLiD was assessed by entering the correlation coefficients for all pairwise comparisons of literacy instruments into a multitrait-multimethod matrix. Internal reliability of TOFHLiD was assessed with Cronbach's alpha. Criterion-related predictive validity was tested by associations between the TOFHLiD scores and the three measures of oral health in multivariate regression analyses. The correlation coefficient for TOFHLiD and REALD-99 scores (monotrait-heteromethod) was high (r = 0.82, P < 0.05). Coefficients between TOFHLiD and TOFHLA (heterotrait-monomethod: r = 0.52) and REALM (heterotrait-heteromethod: r = 0.53) were smaller than coefficients for convergent validity Cronbach's alpha for TOFHLiD was 0.63. TOFHLiD was positively correlated with OHIP-14 (P < 0.05), but not with parent or child oral health. TOFHLA was not related to dental outcomes. TOFHLiD demonstrates good convergent validity but only moderate ability to discriminate between dental and medical health literacy. Its predictive validity is only partially established, and internal consistency just meets the threshold for acceptability. Results provide solid support for more research, but not widespread use in clinical or public

Gene function prediction based on Gene Ontology Hierarchy Preserving Hashing.

PubMed

Zhao, Yingwen; Fu, Guangyuan; Wang, Jun; Guo, Maozu; Yu, Guoxian

2018-02-23

Gene Ontology (GO) uses structured vocabularies (or terms) to describe the molecular functions, biological roles, and cellular locations of gene products in a hierarchical ontology. GO annotations associate genes with GO terms and indicate the given gene products carrying out the biological functions described by the relevant terms. However, predicting correct GO annotations for genes from a massive set of GO terms as defined by GO is a difficult challenge. To combat with this challenge, we introduce a Gene Ontology Hierarchy Preserving Hashing (HPHash) based semantic method for gene function prediction. HPHash firstly measures the taxonomic similarity between GO terms. It then uses a hierarchy preserving hashing technique to keep the hierarchical order between GO terms, and to optimize a series of hashing functions to encode massive GO terms via compact binary codes. After that, HPHash utilizes these hashing functions to project the gene-term association matrix into a low-dimensional one and performs semantic similarity based gene function prediction in the low-dimensional space. Experimental results on three model species (Homo sapiens, Mus musculus and Rattus norvegicus) for interspecies gene function prediction show that HPHash performs better than other related approaches and it is robust to the number of hash functions. In addition, we also take HPHash as a plugin for BLAST based gene function prediction. From the experimental results, HPHash again significantly improves the prediction performance. The codes of HPHash are available at: http://mlda.swu.edu.cn/codes.php?name=HPHash. Copyright © 2018 Elsevier Inc. All rights reserved.

Biochemical tests of placental function for assessment in pregnancy.

PubMed

Neilson, James P

2012-08-15

Biochemical tests of placental or feto-placental function were widely used in the 1960s and 1970s in high-risk pregnancies to try to predict, and thus try to avoid, adverse fetal outcome. To assess the effects of performing biochemical tests of placental function in high-risk, low-risk, or unselected pregnancies. We searched the Cochrane Pregnancy and Childbirth Group's Trials Register (10 May 2012). Controlled trials (randomized or 'quasi-randomized') that compare the use of biochemical tests of placental function in pregnancy with non-use. Trial quality was assessed and data were extracted by the review author. A single eligible trial of poor quality was identified. It involved 622 women with high-risk pregnancies who had had plasma (o)estriol estimations. Women were allocated to have their (o)estriol results revealed or concealed on the basis of hospital record number (with attendant risk of selection bias). There were no obvious differences in perinatal mortality (relative risk (RR) 0.88, 95% confidence interval (CI) 0.36 to 2.13) or planned delivery (RR 0.97, 95% CI 0.81 to 1.15) between the two groups. The available trial data do not support the use of (o)estriol estimation in high-risk pregnancies. The single small trial available does not have the power to exclude a beneficial effect but this is probably of historical interest since biochemical testing has been superseded by biophysical testing in antepartum fetal assessment.

A Survey of Computational Intelligence Techniques in Protein Function Prediction

PubMed Central

Tiwari, Arvind Kumar; Srivastava, Rajeev

2014-01-01

During the past, there was a massive growth of knowledge of unknown proteins with the advancement of high throughput microarray technologies. Protein function prediction is the most challenging problem in bioinformatics. In the past, the homology based approaches were used to predict the protein function, but they failed when a new protein was different from the previous one. Therefore, to alleviate the problems associated with homology based traditional approaches, numerous computational intelligence techniques have been proposed in the recent past. This paper presents a state-of-the-art comprehensive review of various computational intelligence techniques for protein function predictions using sequence, structure, protein-protein interaction network, and gene expression data used in wide areas of applications such as prediction of DNA and RNA binding sites, subcellular localization, enzyme functions, signal peptides, catalytic residues, nuclear/G-protein coupled receptors, membrane proteins, and pathway analysis from gene expression datasets. This paper also summarizes the result obtained by many researchers to solve these problems by using computational intelligence techniques with appropriate datasets to improve the prediction performance. The summary shows that ensemble classifiers and integration of multiple heterogeneous data are useful for protein function prediction. PMID:25574395

The predictive power of physical function assessed by questionnaire and physical performance measures for subsequent disability.

PubMed

Hoshi, Masayuki; Hozawa, Atsushi; Kuriyama, Shinichi; Nakaya, Naoki; Ohmori-Matsuda, Kaori; Sone, Toshimasa; Kakizaki, Masako; Niu, Kaijun; Fujita, Kazuki; Ueki, Shouzoh; Haga, Hiroshi; Nagatomi, Ryoichi; Tsuji, Ichiro

2012-08-01

To compare the predictive power of physical function assessed by questionnaire and physical performance measures for subsequent disability in community-dwelling elderly persons. Prospective cohort study. Participants were 813 aged 70 years and older, elderly Japanese residing in the community, included in the Tsurugaya Project, who were not disabled at the baseline in 2003. Physical function was assessed by the questionnaire of "Motor Fitness Scale". Physical performance measures consisted of maximum walking velocity, timed up and go test (TUG), leg extension power, and functional reach test. The area under the curve (AUC) of the receiver operating characteristic curve for disability was used to compare screening accuracy between Motor Fitness Scale and physical performance measures. Incident disability, defined as certification for long-term care insurance, was used as the endpoint. We observed 135 cases of incident disability during follow-up. The third or fourth quartile for each measure was associated with a significantly increased risk of disability in comparison with the highest quartile. The AUC was 0.70, 0.72, 0.70, 0.68, 0.69 and 0.74, for Motor Fitness Scale, maxi- mum walking velocity, TUG, leg extension power, functional reach test, and total performance score, respectively. The predictive power of physical function assessed by the Motor Fitness Scale was equivalent to that assessed by physical performance measures. Since Motor Fitness Scale can evaluate physical function safely and simply in comparison with physical performance tests, it would be a practical tool for screening persons at high risk of disability.

The evolution of trade-offs: testing predictions on response to selection and environmental variation.

PubMed

Roff, Derek A; Mostowy, Serge; Fairbairn, Daphne J

2002-01-01

The concept of phenotypic trade-offs is a central element in evolutionary theory. In general, phenotypic models assume a fixed trade-off function, whereas quantitative genetic theory predicts that the trade-off function will change as a result of selection. For a linear trade-off function selection will readily change the intercept but will have to be relatively stronger to change the slope. We test these predictions by examining the trade-off between fecundity and flight capability, as measured by dorso-longitudinal muscle mass, in four different populations of the sand cricket, Gryllus firmus. Three populations were recently derived from the wild, and the fourth had been in the laboratory for 19 years. We hypothesized that the laboratory population had most likely undergone more and different selection from the three wild populations and therefore should differ from these in respect to both slope and intercept. Because of geographic variation in selection, we predicted a general difference in intercept among the four populations. We further tested the hypothesis that this intercept will be correlated with proportion macropterous and that this relationship will itself vary with environmental conditions experienced during both the nymphal and adult period. Observed variation in the phenotypic trade-off was consistent with the predictions of the quantitative genetic model. These results point to the importance of modeling trade-offs as dynamic rather than static relationships. We discuss how phenotypic models can incorporate such variation. The phenotypic trade-off between fecundity and dorso-longitudinal muscle mass is determined in part by variation in body size, illustrating the necessity of considering trade-offs to be multi factorial rather than simply bivariate relationships.

14 CFR 35.40 - Functional test.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 1 2014-01-01 2014-01-01 false Functional test. 35.40 Section 35.40... STANDARDS: PROPELLERS Tests and Inspections § 35.40 Functional test. The variable-pitch propeller system must be subjected to the applicable functional tests of this section. The same propeller system used in...

14 CFR 35.40 - Functional test.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 1 2013-01-01 2013-01-01 false Functional test. 35.40 Section 35.40... STANDARDS: PROPELLERS Tests and Inspections § 35.40 Functional test. The variable-pitch propeller system must be subjected to the applicable functional tests of this section. The same propeller system used in...

14 CFR 35.40 - Functional test.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Functional test. 35.40 Section 35.40... STANDARDS: PROPELLERS Tests and Inspections § 35.40 Functional test. The variable-pitch propeller system must be subjected to the applicable functional tests of this section. The same propeller system used in...

Predicting Hydrologic Function With Aquatic Gene Fragments

NASA Astrophysics Data System (ADS)

Good, S. P.; URycki, D. R.; Crump, B. C.

2018-03-01

Recent advances in microbiology techniques, such as genetic sequencing, allow for rapid and cost-effective collection of large quantities of genetic information carried within water samples. Here we posit that the unique composition of aquatic DNA material within a water sample contains relevant information about hydrologic function at multiple temporal scales. In this study, machine learning was used to develop discharge prediction models trained on the relative abundance of bacterial taxa classified into operational taxonomic units (OTUs) based on 16S rRNA gene sequences from six large arctic rivers. We term this approach "genohydrology," and show that OTU relative abundances can be used to predict river discharge at monthly and longer timescales. Based on a single DNA sample from each river, the average Nash-Sutcliffe efficiency (NSE) for predicted mean monthly discharge values throughout the year was 0.84, while the NSE for predicted discharge values across different return intervals was 0.67. These are considerable improvements over predictions based only on the area-scaled mean specific discharge of five similar rivers, which had average NSE values of 0.64 and -0.32 for seasonal and recurrence interval discharge values, respectively. The genohydrology approach demonstrates that genetic diversity within the aquatic microbiome is a large and underutilized data resource with benefits for prediction of hydrologic function.

Differential Prediction Generalization in College Admissions Testing

ERIC Educational Resources Information Center

Aguinis, Herman; Culpepper, Steven A.; Pierce, Charles A.

2016-01-01

We introduce the concept of "differential prediction generalization" in the context of college admissions testing. Specifically, we assess the extent to which predicted first-year college grade point average (GPA) based on high-school grade point average (HSGPA) and SAT scores depends on a student's ethnicity and gender and whether this…

Can Functional Movement Assessment Predict Football Head Impact Biomechanics?

PubMed

Ford, Julia M; Campbell, Kody R; Ford, Cassie B; Boyd, Kenneth E; Padua, Darin A; Mihalik, Jason P

2018-06-01

The purposes of this study was to determine functional movement assessments' ability to predict head impact biomechanics in college football players and to determine whether head impact biomechanics could explain preseason to postseason changes in functional movement performance. Participants (N = 44; mass, 109.0 ± 20.8 kg; age, 20.0 ± 1.3 yr) underwent two preseason and postseason functional movement assessment screenings: 1) Fusionetics Movement Efficiency Test and 2) Landing Error Scoring System (LESS). Fusionetics is scored 0 to 100, and participants were categorized into the following movement quality groups as previously published: good (≥75), moderate (50-75), and poor (<50). The LESS is scored 0 to 17, and participants were categorized into the following previously published movement quality groups: good (≤5 errors), moderate (6-7 errors), and poor (>7 errors). The Head Impact Telemetry (HIT) System measured head impact frequency and magnitude (linear acceleration and rotational acceleration). An encoder with six single-axis accelerometers was inserted between the padding of a commercially available Riddell football helmet. We used random intercepts general linear-mixed models to analyze our data. There were no effects of preseason movement assessment group on the two Head Impact Telemetry System impact outcomes: linear acceleration and rotational acceleration. Head impact frequency did not significantly predict preseason to postseason score changes obtained from the Fusionetics (F1,36 = 0.22, P = 0.643, R = 0.006) or the LESS (F1,36 < 0.01, P = 0.988, R < 0.001) assessments. Previous research has demonstrated an association between concussion and musculoskeletal injury, as well as functional movement assessment performance and musculoskeletal injury. The functional movement assessments chosen may not be sensitive enough to detect neurological and neuromuscular differences within the sample and subtle changes after sustaining head impacts.

Cycling Power Outputs Predict Functional Threshold Power And Maximum Oxygen Uptake.

PubMed

Denham, Joshua; Scott-Hamilton, John; Hagstrom, Amanda D; Gray, Adrian J

2017-09-11

Functional threshold power (FTP) has emerged as a correlate of lactate threshold and is commonly assessed by recreational and professional cyclists for tailored exercise programing. To identify whether results from traditional aerobic and anaerobic cycling tests could predict FTP and V˙ O2max, we analysed the association between estimated FTP, maximum oxygen uptake (V˙ O2max [mlkgmin]) and power outputs obtained from a maximal cycle ergometry cardiopulmonary exercise test (CPET) and a 30-s Wingate test in a heterogeneous cohort of cycle-trained and untrained individuals (N=40, mean±SD; age: 32.6±10.6 y; relative V˙ O2max: 46.8±9.1 mlkgmin). The accuracy and sensitivity of the prediction equations was also assessed in young men (N=11) before and after a 6-wk sprint interval training intervention.Moderate to strong positive correlations were observed between FTP, relative V˙ O2max and power outputs achieved during incremental and 30-s Wingate cycling tests (r=.39-.965, all P<.05). While maximum power achieved during incremental cycle testing (Pmax) and relative V˙ O2max were predictors of FTP (r =.93), age and FTP (Wkg) estimated relative V˙ O2max (r=.80). Our findings confirm that FTP predominantly relies on aerobic metabolism and indicate both prediction models are sensitive enough to detect meaningful exercise-induced changes in FTP and V˙ O2max. Thus, coaches should consider limiting the time and load demands placed on athletes by conducting a maximal cycle ergometry CPET to estimate FTP. Additionally, a 20-min FTP test is a convenient method to assess V˙ O2max and is particularly relevant for exercise professionals without access to expensive CPET equipment.

Combining Spot Sign and Intracerebral Hemorrhage Score to Estimate Functional Outcome: Analysis From the PREDICT Cohort.

PubMed

Schneider, Hauke; Huynh, Thien J; Demchuk, Andrew M; Dowlatshahi, Dar; Rodriguez-Luna, David; Silva, Yolanda; Aviv, Richard; Dzialowski, Imanuel

2018-06-01

The intracerebral hemorrhage (ICH) score is the most commonly used grading scale for stratifying functional outcome in patients with acute ICH. We sought to determine whether a combination of the ICH score and the computed tomographic angiography spot sign may improve outcome prediction in the cohort of a prospective multicenter hemorrhage trial. Prospectively collected data from 241 patients from the observational PREDICT study (Prediction of Hematoma Growth and Outcome in Patients With Intracerebral Hemorrhage Using the CT-Angiography Spot Sign) were analyzed. Functional outcome at 3 months was dichotomized using the modified Rankin Scale (0-3 versus 4-6). Performance of (1) the ICH score and (2) the spot sign ICH score-a scoring scale combining ICH score and spot sign number-was tested. Multivariable analysis demonstrated that ICH score (odds ratio, 3.2; 95% confidence interval, 2.2-4.8) and spot sign number (n=1: odds ratio, 2.7; 95% confidence interval, 1.1-7.4; n>1: odds ratio, 3.8; 95% confidence interval, 1.2-17.1) were independently predictive of functional outcome at 3 months with similar odds ratios. Prediction of functional outcome was not significantly different using the spot sign ICH score compared with the ICH score alone (spot sign ICH score area under curve versus ICH score area under curve: P =0.14). In the PREDICT cohort, a prognostic score adding the computed tomographic angiography-based spot sign to the established ICH score did not improve functional outcome prediction compared with the ICH score. © 2018 American Heart Association, Inc.

Arc Jet Facility Test Condition Predictions Using the ADSI Code

NASA Technical Reports Server (NTRS)

Palmer, Grant; Prabhu, Dinesh; Terrazas-Salinas, Imelda

2015-01-01

The Aerothermal Design Space Interpolation (ADSI) tool is used to interpolate databases of previously computed computational fluid dynamic solutions for test articles in a NASA Ames arc jet facility. The arc jet databases are generated using an Navier-Stokes flow solver using previously determined best practices. The arc jet mass flow rates and arc currents used to discretize the database are chosen to span the operating conditions possible in the arc jet, and are based on previous arc jet experimental conditions where possible. The ADSI code is a database interpolation, manipulation, and examination tool that can be used to estimate the stagnation point pressure and heating rate for user-specified values of arc jet mass flow rate and arc current. The interpolation is performed in the other direction (predicting mass flow and current to achieve a desired stagnation point pressure and heating rate). ADSI is also used to generate 2-D response surfaces of stagnation point pressure and heating rate as a function of mass flow rate and arc current (or vice versa). Arc jet test data is used to assess the predictive capability of the ADSI code.

Ethical Issues of Predictive Genetic Testing for Diabetes

PubMed Central

Haga, Susanne B.

2009-01-01

With the rising number of individuals affected with diabetes and the significant health care costs of treatment, the emphasis on prevention is key to controlling the health burden of this disease. Several genetic and genomic studies have identified genetic variants associated with increased risk to diabetes. As a result, commercial testing is available to predict an individual's genetic risk. Although the clinical benefits of testing have not yet been demonstrated, it is worth considering some of the ethical implications of testing for this common chronic disease. In this article, I discuss several issues that should be considered during the translation of predictive testing for diabetes, including familial implications, improvement of risk communication, implications for behavioral change and health outcomes, the Genetic Information Nondiscrimination Act, direct-to-consumer testing, and appropriate age of testing. PMID:20144329

The Protein Interactome of Mycobacteriophage Giles Predicts Functions for Unknown Proteins.

PubMed

Mehla, Jitender; Dedrick, Rebekah M; Caufield, J Harry; Siefring, Rachel; Mair, Megan; Johnson, Allison; Hatfull, Graham F; Uetz, Peter

2015-08-01

Mycobacteriophages are viruses that infect mycobacterial hosts and are prevalent in the environment. Nearly 700 mycobacteriophage genomes have been completely sequenced, revealing considerable diversity and genetic novelty. Here, we have determined the protein complement of mycobacteriophage Giles by mass spectrometry and mapped its genome-wide protein interactome to help elucidate the roles of its 77 predicted proteins, 50% of which have no known function. About 22,000 individual yeast two-hybrid (Y2H) tests with four different Y2H vectors, followed by filtering and retest screens, resulted in 324 reproducible protein-protein interactions, including 171 (136 nonredundant) high-confidence interactions. The complete set of high-confidence interactions among Giles proteins reveals new mechanistic details and predicts functions for unknown proteins. The Giles interactome is the first for any mycobacteriophage and one of just five known phage interactomes so far. Our results will help in understanding mycobacteriophage biology and aid in development of new genetic and therapeutic tools to understand Mycobacterium tuberculosis. Mycobacterium tuberculosis causes over 9 million new cases of tuberculosis each year. Mycobacteriophages, viruses of mycobacterial hosts, hold considerable potential to understand phage diversity, evolution, and mycobacterial biology, aiding in the development of therapeutic tools to control mycobacterial infections. The mycobacteriophage Giles protein-protein interaction network allows us to predict functions for unknown proteins and shed light on major biological processes in phage biology. For example, Giles gp76, a protein of unknown function, is found to associate with phage packaging and maturation. The functions of mycobacteriophage-derived proteins may suggest novel therapeutic approaches for tuberculosis. Our ORFeome clone set of Giles proteins and the interactome data will be useful resources for phage interactomics. Copyright © 2015

A test to evaluate the earthquake prediction algorithm, M8

USGS Publications Warehouse

Healy, John H.; Kossobokov, Vladimir G.; Dewey, James W.

1992-01-01

A test of the algorithm M8 is described. The test is constructed to meet four rules, which we propose to be applicable to the test of any method for earthquake prediction:  1. An earthquake prediction technique should be presented as a well documented, logical algorithm that can be used by  investigators without restrictions. 2. The algorithm should be coded in a common programming language and implementable on widely available computer systems. 3. A test of the earthquake prediction technique should involve future predictions with a black box version of the algorithm in which potentially adjustable parameters are fixed in advance. The source of the input data must be defined and ambiguities in these data must be resolved automatically by the algorithm. 4. At least one reasonable null hypothesis should be stated in advance of testing the earthquake prediction method, and it should be stated how this null hypothesis will be used to estimate the statistical significance of the earthquake predictions. The M8 algorithm has successfully predicted several destructive earthquakes, in the sense that the earthquakes occurred inside regions with linear dimensions from 384 to 854 km that the algorithm had identified as being in times of increased probability for strong earthquakes. In addition, M8 has successfully "post predicted" high percentages of strong earthquakes in regions to which it has been applied in retroactive studies. The statistical significance of previous predictions has not been established, however, and post-prediction studies in general are notoriously subject to success-enhancement through hindsight. Nor has it been determined how much more precise an M8 prediction might be than forecasts and probability-of-occurrence estimates made by other techniques. We view our test of M8 both as a means to better determine the effectiveness of M8 and as an experimental structure within which to make observations that might lead to improvements in the algorithm

Prediction of Chemical Function: Model Development and ...

EPA Pesticide Factsheets

The United States Environmental Protection Agency’s Exposure Forecaster (ExpoCast) project is developing both statistical and mechanism-based computational models for predicting exposures to thousands of chemicals, including those in consumer products. The high-throughput (HT) screening-level exposures developed under ExpoCast can be combined with HT screening (HTS) bioactivity data for the risk-based prioritization of chemicals for further evaluation. The functional role (e.g. solvent, plasticizer, fragrance) that a chemical performs can drive both the types of products in which it is found and the concentration in which it is present and therefore impacting exposure potential. However, critical chemical use information (including functional role) is lacking for the majority of commercial chemicals for which exposure estimates are needed. A suite of machine-learning based models for classifying chemicals in terms of their likely functional roles in products based on structure were developed. This effort required collection, curation, and harmonization of publically-available data sources of chemical functional use information from government and industry bodies. Physicochemical and structure descriptor data were generated for chemicals with function data. Machine-learning classifier models for function were then built in a cross-validated manner from the descriptor/function data using the method of random forests. The models were applied to: 1) predict chemi

Prediction of Academic Achievement with the McCarthy Screening Test and Metropolitan Readiness Test.

ERIC Educational Resources Information Center

Gullo, Dominic F.; And Others

1984-01-01

Examined the efficacy of the McCarthy Screening Test (MST) and Metropolitan Readiness Test (MRT) to predict academic readiness after kindergarten and achievement at the end of first grade. The MST significantly predicted children's scores of the MRT and SFAT. Additionally, the MRT was a significant predictor of the SFAT. (JAC)

Human mobility prediction from region functions with taxi trajectories.

PubMed

Wang, Minjie; Yang, Su; Sun, Yi; Gao, Jun

2017-01-01

People in cities nowadays suffer from increasingly severe traffic jams due to less awareness of how collective human mobility is affected by urban planning. Besides, understanding how region functions shape human mobility is critical for business planning but remains unsolved so far. This study aims to discover the association between region functions and resulting human mobility. We establish a linear regression model to predict the traffic flows of Beijing based on the input referred to as bag of POIs. By solving the predictor in the sense of sparse representation, we find that the average prediction precision is over 74% and each type of POI contributes differently in the predictor, which accounts for what factors and how such region functions attract people visiting. Based on these findings, predictive human mobility could be taken into account when planning new regions and region functions.

Human mobility prediction from region functions with taxi trajectories

PubMed Central

Wang, Minjie; Sun, Yi; Gao, Jun

2017-01-01

People in cities nowadays suffer from increasingly severe traffic jams due to less awareness of how collective human mobility is affected by urban planning. Besides, understanding how region functions shape human mobility is critical for business planning but remains unsolved so far. This study aims to discover the association between region functions and resulting human mobility. We establish a linear regression model to predict the traffic flows of Beijing based on the input referred to as bag of POIs. By solving the predictor in the sense of sparse representation, we find that the average prediction precision is over 74% and each type of POI contributes differently in the predictor, which accounts for what factors and how such region functions attract people visiting. Based on these findings, predictive human mobility could be taken into account when planning new regions and region functions. PMID:29190708

A large-scale evaluation of computational protein function prediction

PubMed Central

Radivojac, Predrag; Clark, Wyatt T; Ronnen Oron, Tal; Schnoes, Alexandra M; Wittkop, Tobias; Sokolov, Artem; Graim, Kiley; Funk, Christopher; Verspoor, Karin; Ben-Hur, Asa; Pandey, Gaurav; Yunes, Jeffrey M; Talwalkar, Ameet S; Repo, Susanna; Souza, Michael L; Piovesan, Damiano; Casadio, Rita; Wang, Zheng; Cheng, Jianlin; Fang, Hai; Gough, Julian; Koskinen, Patrik; Törönen, Petri; Nokso-Koivisto, Jussi; Holm, Liisa; Cozzetto, Domenico; Buchan, Daniel W A; Bryson, Kevin; Jones, David T; Limaye, Bhakti; Inamdar, Harshal; Datta, Avik; Manjari, Sunitha K; Joshi, Rajendra; Chitale, Meghana; Kihara, Daisuke; Lisewski, Andreas M; Erdin, Serkan; Venner, Eric; Lichtarge, Olivier; Rentzsch, Robert; Yang, Haixuan; Romero, Alfonso E; Bhat, Prajwal; Paccanaro, Alberto; Hamp, Tobias; Kassner, Rebecca; Seemayer, Stefan; Vicedo, Esmeralda; Schaefer, Christian; Achten, Dominik; Auer, Florian; Böhm, Ariane; Braun, Tatjana; Hecht, Maximilian; Heron, Mark; Hönigschmid, Peter; Hopf, Thomas; Kaufmann, Stefanie; Kiening, Michael; Krompass, Denis; Landerer, Cedric; Mahlich, Yannick; Roos, Manfred; Björne, Jari; Salakoski, Tapio; Wong, Andrew; Shatkay, Hagit; Gatzmann, Fanny; Sommer, Ingolf; Wass, Mark N; Sternberg, Michael J E; Škunca, Nives; Supek, Fran; Bošnjak, Matko; Panov, Panče; Džeroski, Sašo; Šmuc, Tomislav; Kourmpetis, Yiannis A I; van Dijk, Aalt D J; ter Braak, Cajo J F; Zhou, Yuanpeng; Gong, Qingtian; Dong, Xinran; Tian, Weidong; Falda, Marco; Fontana, Paolo; Lavezzo, Enrico; Di Camillo, Barbara; Toppo, Stefano; Lan, Liang; Djuric, Nemanja; Guo, Yuhong; Vucetic, Slobodan; Bairoch, Amos; Linial, Michal; Babbitt, Patricia C; Brenner, Steven E; Orengo, Christine; Rost, Burkhard; Mooney, Sean D; Friedberg, Iddo

2013-01-01

Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based Critical Assessment of protein Function Annotation (CAFA) experiment. Fifty-four methods representing the state-of-the-art for protein function prediction were evaluated on a target set of 866 proteins from eleven organisms. Two findings stand out: (i) today’s best protein function prediction algorithms significantly outperformed widely-used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is significant need for improvement of currently available tools. PMID:23353650

Using liver enzymes as screening tests to predict mortality risk.

PubMed

Fulks, Michael; Stout, Robert L; Dolan, Vera F

2008-01-01

Determine the relationship between liver function test results (GGT, alkaline phosphatase, AST, and ALT) and all-cause mortality in life insurance applicants. By use of the Social Security Master Death File, mortality was examined in 1,905,664 insurance applicants for whom blood samples were submitted to the Clinical Reference Laboratory. There were 50,174 deaths observed in this study population. Results were stratified by 3 age/sex groups: females, age <60; males, age <60; and all, age 60+. Liver function test values were grouped using percentiles of their distribution in these 3 age/sex groups, as well as ranges of actual values. Using the risk of the middle 50% of the population by distribution as a reference, relative mortality observed for GGT and alkaline phosphatase was linear with a steep slope from very low to relatively high values. Relative mortality was increased at lower values for both AST and ALT. ALT did not predict mortality for values above the middle 50% of its distribution. GGT and alkaline phosphatase are significant predictors of mortality risk for all values. ALT is still useful for triggering further testing for hepatitis, but AST should be used instead to assess mortality risk linked with transaminases.

Pretest Predictions for Ventilation Tests

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

Y. Sun; H. Yang; H.N. Kalia

The objective of this calculation is to predict the temperatures of the ventilating air, waste package surface, concrete pipe walls, and insulation that will be developed during the ventilation tests involving various test conditions. The results will be used as input to the following three areas: (1) Decisions regarding testing set-up and performance. (2) Assessing how best to scale the test phenomena measured. (3) Validating numerical approach for modeling continuous ventilation. The scope of the calculation is to identify the physical mechanisms and parameters related to thermal response in the ventilation tests, and develop and describe numerical methods that canmore » be used to calculate the effects of continuous ventilation. Sensitivity studies to assess the impact of variation of linear power densities (linear heat loads) and ventilation air flow rates are included. The calculation is limited to thermal effect only.« less

Doppler echocardiographic myocardial stunning index predicts recovery of left ventricular systolic function after primary percutaneous coronary intervention.

PubMed

Sharif, Dawod; Matanis, Wisam; Sharif-Rasslan, Amal; Rosenschein, Uri

2016-10-01

Myocardial stunning is responsible for partially reversible left ventricular (LV) systolic dysfunction after successful primary percutaneous coronary intervention (PPCI) in patients with acute ST-elevation myocardial infarction (STEMI). To test the hypothesis that early coronary blood flow (CBF) to LV systolic function ratios, as an equivalent to LV stunning index (SI), predict recovery of LV systolic function after PPCI in patients with acute STEMI. Twenty-four patients with acute anterior STEMI who had successful PPCI were evaluated and compared to 96 control subjects. Transthoracic echocardiography with measurement of LV ejection fraction (EF), LV, and left anterior descending (LAD) coronary artery area wall-motion score index (WMSI) as well as Doppler sampling of LAD blood velocities, early after PPCI and 5 days later, were performed. SI was evaluated as the early ratio of CBF parameters in the LAD to LV systolic function parameters. Early SI-LVEF well predicted late LVEF (r=.51, P<.01) and the change in LVEF (r=.48, P<.017). Early SI-LVMSI predicted well late LVEF (r=.56, P<.006) and the change in LVEF (r=.46, P<.028). Early SI-LADWMSI predicted late LVEF (r=.44, P<.028). Other SI indices measured as other LAD-CBF to LV systolic function parameters were not predictive of late LV systolic function. LV stunning indices measured as early LAD flow to LVEF, LVWMSI, and LADWMSI ratios well predicted late LVEF and the change in LVEF. Thus, greater early coronary artery flow to LV systolic function parameter ratios predict a better improvement in late LV systolic function after PPCI. © 2016, Wiley Periodicals, Inc.

Accuracy of indocyanine green pulse spectrophotometry clearance test for liver function prediction in transplanted patients

PubMed Central

Hsieh, Chung-Bao; Chen, Chung-Jueng; Chen, Teng-Wei; Yu, Jyh-Cherng; Shen, Kuo-Liang; Chang, Tzu-Ming; Liu, Yao-Chi

2004-01-01

AIM: To investigate whether the non-invasive real-time Indocynine green (ICG) clearance is a sensitive index of liver viability in patients before, during, and after liver transplantation. METHODS: Thirteen patients were studied, two before, three during, and eight following liver transplantation, with two patients suffering acute rejection. The conventional invasive ICG clearance test and ICG pulse spectrophotometry non-invasive real-time ICG clearance test were performed simultaneously. Using linear regression analysis we tested the correlation between these two methods. The transplantation condition of these patients and serum total bilirubin (T. Bil), alanine aminotransferase (ALT), and platelet count were also evaluated. RESULTS: The correlation between these two methods was excellent (r2 = 0.977). CONCLUSION: ICG pulse spectrophotometry clearance is a quick, non-invasive, and reliable liver function test in transplantation patients. PMID:15285026

Cognitive Impairment Precedes and Predicts Functional Impairment in Mild Alzheimer's Disease.

PubMed

Liu-Seifert, Hong; Siemers, Eric; Price, Karen; Han, Baoguang; Selzler, Katherine J; Henley, David; Sundell, Karen; Aisen, Paul; Cummings, Jeffrey; Raskin, Joel; Mohs, Richard

2015-01-01

The temporal relationship of cognitive deficit and functional impairment in Alzheimer's disease (AD) is not well characterized. Recent analyses suggest cognitive decline predicts subsequent functional decline throughout AD progression. To better understand the relationship between cognitive and functional decline in mild AD using autoregressive cross-lagged (ARCL) panel analyses in several clinical trials. Data included placebo patients with mild AD pooled from two multicenter, double-blind, Phase 3 solanezumab (EXPEDITION/2) or semagacestat (IDENTITY/2) studies, and from AD patients participating in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Cognitive and functional outcomes were assessed using AD Assessment Scale-Cognitive subscale (ADAS-Cog), AD Cooperative Study-Activities of Daily Living instrumental subscale (ADCS-iADL), or Functional Activities Questionnaire (FAQ), respectively. ARCL panel analyses evaluated relationships between cognitive and functional impairment over time. In EXPEDITION, ARCL panel analyses demonstrated cognitive scores significantly predicted future functional impairment at 5 of 6 time points, while functional scores predicted subsequent cognitive scores in only 1 of 6 time points. Data from IDENTITY and ADNI programs yielded consistent results whereby cognition predicted subsequent function, but not vice-versa. Analyses from three databases indicated cognitive decline precedes and predicts subsequent functional decline in mild AD dementia, consistent with previously proposed hypotheses, and corroborate recent publications using similar methodologies. Cognitive impairment may be used as a predictor of future functional impairment in mild AD dementia and can be considered a critical target for prevention strategies to limit future functional decline in the dementia process.

Computational Prediction of the Global Functional Genomic Landscape: Applications, Methods and Challenges

PubMed Central

Zhou, Weiqiang; Sherwood, Ben; Ji, Hongkai

2017-01-01

Technological advances have led to an explosive growth of high-throughput functional genomic data. Exploiting the correlation among different data types, it is possible to predict one functional genomic data type from other data types. Prediction tools are valuable in understanding the relationship among different functional genomic signals. They also provide a cost-efficient solution to inferring the unknown functional genomic profiles when experimental data are unavailable due to resource or technological constraints. The predicted data may be used for generating hypotheses, prioritizing targets, interpreting disease variants, facilitating data integration, quality control, and many other purposes. This article reviews various applications of prediction methods in functional genomics, discusses analytical challenges, and highlights some common and effective strategies used to develop prediction methods for functional genomic data. PMID:28076869

[Study of the predictive value of detection tests for silent aspirations].

PubMed

Woisard, V; Réhault, E; Brouard, C; Fichaux-Bourin, P; Puech, M; Grand, S

2009-01-01

Screening for aspiration in patients with swallowing disorders is important in preventing complications. The tests used in this regard are insufficient due to silent aspiration relating to abnormal protective reflexes in many patients with swallowing problems. The aim of this study is to determine the predictive values of simple tests in screening for silent aspiration. The reference test used was videofluoroscopic examination on swallowing. In the presence of aspiration (FR+) the presence (ME+) or not (ME-) of a cough of throat clearing was noted. The tests being studied were a nasal test with isotonic saline and swallowing according to a set time. For screening for aspiration the presence of a "wet voice" was considered to be a sign of reduced protective reflexes. 1) During the nasal test, the results are 100% for the positive predictive value (VPp) and 83.3% for the negative predictive value (VPn); 2) These results are respectively 84.6% and 35.9% during the swallowing test. Regarding screening for silent aspiration, 1) during the nasal test, the results are 62.5% for the positive predictive value (VPp) and 36.3% for the negative predictive value (VPn); 2) These results are respectively 54.5% and 26.6% during the swallowing test. This preliminary study points out the lack of predictive value of the nasal test and the swallow test for the silent aspirations. However the results could be useful for other researchers developing other tests in this area.

Track/train dynamics test procedure transfer function test

NASA Technical Reports Server (NTRS)

Vigil, R. A.

1975-01-01

A transfer function vibration test was made on an 80 ton open hopper freight car in an effort to obtain validation data on the car's nonlinear elastic model. Test configuration, handling, test facilities, test operations, and data acquisition/reduction activities necessary to meet the conditions of test requirements are given.

Validation and clinical utility of the executive function performance test in persons with traumatic brain injury.

PubMed

Baum, C M; Wolf, T J; Wong, A W K; Chen, C H; Walker, K; Young, A C; Carlozzi, N E; Tulsky, D S; Heaton, R K; Heinemann, A W

2017-07-01

This study examined the relationships between the Executive Function Performance Test (EFPT), the NIH Toolbox Cognitive Function tests, and neuropsychological executive function measures in 182 persons with traumatic brain injury (TBI) and 46 controls to evaluate construct, discriminant, and predictive validity. Construct validity: There were moderate correlations between the EFPT and the NIH Toolbox Crystallized (r = -.479), Fluid Tests (r = -.420), and Total Composite Scores (r = -.496). Discriminant validity: Significant differences were found in the EFPT total and sequence scores across control, complicated mild/moderate, and severe TBI groups. We found differences in the organisation score between control and severe, and between mild and severe TBI groups. Both TBI groups had significantly lower scores in safety and judgement than controls. Compared to the controls, the severe TBI group demonstrated significantly lower performance on all instrumental activities of daily living (IADL) tasks. Compared to the mild TBI group, the controls performed better on the medication task, the severe TBI group performed worse in the cooking and telephone tasks. Predictive validity: The EFPT predicted the self-perception of independence measured by the TBI-QOL (beta = -0.49, p < .001) for the severe TBI group. Overall, these data support the validity of the EFPT for use in individuals with TBI.

14 CFR 35.40 - Functional test.

Code of Federal Regulations, 2012 CFR

2012-01-01

... representative engine on a test stand or on an airplane. The propeller must complete these tests without evidence... STANDARDS: PROPELLERS Tests and Inspections § 35.40 Functional test. The variable-pitch propeller system must be subjected to the applicable functional tests of this section. The same propeller system used in...

14 CFR 35.40 - Functional test.

Code of Federal Regulations, 2011 CFR

2011-01-01

... representative engine on a test stand or on an airplane. The propeller must complete these tests without evidence... STANDARDS: PROPELLERS Tests and Inspections § 35.40 Functional test. The variable-pitch propeller system must be subjected to the applicable functional tests of this section. The same propeller system used in...

Expansion tube test time predictions

NASA Technical Reports Server (NTRS)

Gourlay, Christopher M.

1988-01-01

The interaction of an interface between two gases and strong expansion is investigated and the effect on flow in an expansion tube is examined. Two mechanisms for the unsteady Pitot-pressure fluctuations found in the test section of an expansion tube are proposed. The first mechanism depends on the Rayleigh-Taylor instability of the driver-test gas interface in the presence of a strong expansion. The second mechanism depends on the reflection of the strong expansion from the interface. Predictions compare favorably with experimental results. The theory is expected to be independent of the absolute values of the initial expansion tube filling pressures.

[Interpretation and use of routine pulmonary function tests: Spirometry, static lung volumes, lung diffusion, arterial blood gas, methacholine challenge test and 6-minute walk test].

PubMed

Bokov, P; Delclaux, C

2016-02-01

Resting pulmonary function tests (PFT) include the assessment of ventilatory capacity: spirometry (forced expiratory flows and mobilisable volumes) and static volume assessment, notably using body plethysmography. Spirometry allows the potential definition of obstructive defect, while static volume assessment allows the potential definition of restrictive defect (decrease in total lung capacity) and thoracic hyperinflation (increase in static volumes). It must be kept in mind that this evaluation is incomplete and that an assessment of ventilatory demand is often warranted, especially when facing dyspnoea: evaluation of arterial blood gas (searching for respiratory insufficiency) and measurement of the transfer coefficient of the lung, allowing with the measurement of alveolar volume to calculate the diffusing capacity of the lung for CO (DLCO: assessment of alveolar-capillary wall and capillary blood volume). All these pulmonary function tests have been the subject of an Americano-European Task force (standardisation of lung function testing) published in 2005, and translated in French in 2007. Interpretative strategies for lung function tests have been recommended, which define abnormal lung function tests using the 5th and 95th percentiles of predicted values (lower and upper limits of normal values). Thus, these recommendations need to be implemented in all pulmonary function test units. A methacholine challenge test will only be performed in the presence of an intermediate pre-test probability for asthma (diagnostic uncertainty), which is an infrequent setting. The most convenient exertional test is the 6-minute walk test that allows the assessment of walking performance, the search for arterial desaturation and the quantification of dyspnoea complaint. Copyright © 2015 Société nationale française de médecine interne (SNFMI). Published by Elsevier SAS. All rights reserved.

Daily Spouse Responsiveness Predicts Longer-Term Trajectories of Physical Function

PubMed Central

Wilson, Stephanie J.; Martire, Lynn M.; Sliwinski, Martin J.

2017-01-01

Everyday interpersonal experiences may underlie the well-established link between close relationships and physical health, but multitemporal designs necessary for strong conclusions about temporal sequence are rare. The current study of 145 knee osteoarthritis patients and their spouses focused on a novel pattern in everyday interactions, daily spouse responsiveness—the degree to which spouse responses are calibrated to changes in patients’ everyday verbal pain expression. Using couple-level slopes, multilevel latent-variable growth models tested associations between three types of daily spouse responsiveness (empathic, solicitous, and punishing), as measured during a 3-week experience-sampling study, and change in patient physical function across 18 months. As predicted, patients whose spouses were more empathically responsive to their pain expression showed better physical function over time compared to those whose spouses were less empathically responsive. This study points to daily responsiveness, a theoretically rooted operationalization of spouse sensitivity, as important for long-term changes in objective physical function. PMID:28459650

Utility functions predict variance and skewness risk preferences in monkeys

PubMed Central

Genest, Wilfried; Stauffer, William R.; Schultz, Wolfram

2016-01-01

Utility is the fundamental variable thought to underlie economic choices. In particular, utility functions are believed to reflect preferences toward risk, a key decision variable in many real-life situations. To assess the validity of utility representations, it is therefore important to examine risk preferences. In turn, this approach requires formal definitions of risk. A standard approach is to focus on the variance of reward distributions (variance-risk). In this study, we also examined a form of risk related to the skewness of reward distributions (skewness-risk). Thus, we tested the extent to which empirically derived utility functions predicted preferences for variance-risk and skewness-risk in macaques. The expected utilities calculated for various symmetrical and skewed gambles served to define formally the direction of stochastic dominance between gambles. In direct choices, the animals’ preferences followed both second-order (variance) and third-order (skewness) stochastic dominance. Specifically, for gambles with different variance but identical expected values (EVs), the monkeys preferred high-variance gambles at low EVs and low-variance gambles at high EVs; in gambles with different skewness but identical EVs and variances, the animals preferred positively over symmetrical and negatively skewed gambles in a strongly transitive fashion. Thus, the utility functions predicted the animals’ preferences for variance-risk and skewness-risk. Using these well-defined forms of risk, this study shows that monkeys’ choices conform to the internal reward valuations suggested by their utility functions. This result implies a representation of utility in monkeys that accounts for both variance-risk and skewness-risk preferences. PMID:27402743

Utility functions predict variance and skewness risk preferences in monkeys.

PubMed

Genest, Wilfried; Stauffer, William R; Schultz, Wolfram

2016-07-26

Utility is the fundamental variable thought to underlie economic choices. In particular, utility functions are believed to reflect preferences toward risk, a key decision variable in many real-life situations. To assess the validity of utility representations, it is therefore important to examine risk preferences. In turn, this approach requires formal definitions of risk. A standard approach is to focus on the variance of reward distributions (variance-risk). In this study, we also examined a form of risk related to the skewness of reward distributions (skewness-risk). Thus, we tested the extent to which empirically derived utility functions predicted preferences for variance-risk and skewness-risk in macaques. The expected utilities calculated for various symmetrical and skewed gambles served to define formally the direction of stochastic dominance between gambles. In direct choices, the animals' preferences followed both second-order (variance) and third-order (skewness) stochastic dominance. Specifically, for gambles with different variance but identical expected values (EVs), the monkeys preferred high-variance gambles at low EVs and low-variance gambles at high EVs; in gambles with different skewness but identical EVs and variances, the animals preferred positively over symmetrical and negatively skewed gambles in a strongly transitive fashion. Thus, the utility functions predicted the animals' preferences for variance-risk and skewness-risk. Using these well-defined forms of risk, this study shows that monkeys' choices conform to the internal reward valuations suggested by their utility functions. This result implies a representation of utility in monkeys that accounts for both variance-risk and skewness-risk preferences.

Comparative analysis of grapevine whole-genome gene predictions, functional annotation, categorization and integration of the predicted gene sequences

PubMed Central

2012-01-01

Background The first draft assembly and gene prediction of the grapevine genome (8X base coverage) was made available to the scientific community in 2007, and functional annotation was developed on this gene prediction. Since then additional Sanger sequences were added to the 8X sequences pool and a new version of the genomic sequence with superior base coverage (12X) was produced. Results In order to more efficiently annotate the function of the genes predicted in the new assembly, it is important to build on as much of the previous work as possible, by transferring 8X annotation of the genome to the 12X version. The 8X and 12X assemblies and gene predictions of the grapevine genome were compared to answer the question, “Can we uniquely map 8X predicted genes to 12X predicted genes?” The results show that while the assemblies and gene structure predictions are too different to make a complete mapping between them, most genes (18,725) showed a one-to-one relationship between 8X predicted genes and the last version of 12X predicted genes. In addition, reshuffled genomic sequence structures appeared. These highlight regions of the genome where the gene predictions need to be taken with caution. Based on the new grapevine gene functional annotation and in-depth functional categorization, twenty eight new molecular networks have been created for VitisNet while the existing networks were updated. Conclusions The outcomes of this study provide a functional annotation of the 12X genes, an update of VitisNet, the system of the grapevine molecular networks, and a new functional categorization of genes. Data are available at the VitisNet website (http://www.sdstate.edu/ps/research/vitis/pathways.cfm). PMID:22554261

Testing the predictive power of cognitive atypicalities in autistic children: evidence from a 3-year follow-up study.

PubMed

Pellicano, Elizabeth

2013-08-01

This follow-up study investigated the predictive power of early cognitive atypicalities. Specifically, it examined whether early individual differences in specific cognitive skills, including theory of mind, executive function, and central coherence, could uniquely account for variation in autistic children's behaviors-social communication, repetitive behaviors, and interests and insistence on sameness-at follow-up. Thirty-seven cognitively able children with an autism spectrum condition were assessed on tests tapping verbal and nonverbal ability, theory of mind (false-belief prediction), executive function (planning ability, cognitive flexibility, and inhibitory control), and central coherence (local processing) at intake and their behavioral functioning (social communication, repetitive behaviors and interests, insistence on sameness) 3 years later. Individual differences in early executive but not theory of mind skills predicted variation in children's social communication. Individual differences in children's early executive function also predicted the degree of repetitive behaviors and interests at follow-up. There were no predictive relationships between early central coherence and children's insistence on sameness. These findings challenge the notion that distinct cognitive atypicalities map on to specific behavioral features of autism. Instead, early variation in executive function plays a key role in helping to shape autistic children's emerging behaviors, including their social communication and repetitive behaviors and interests. © 2013 International Society for Autism Research, Wiley Periodicals, Inc.

Ability of three motor measures to predict functional outcomes reported by stroke patients after rehabilitation.

PubMed

Li, Kuan-Yi; Lin, Keh-Chung; Wang, Tien-Ni; Wu, Ching-Yi; Huang, Yan-Hua; Ouyang, Pei

2012-01-01

This investigation examined the demographic characteristics along with 3 measures of motor function in determining outcomes in activities of daily living (ADL) after distributed constraint-induced therapy (dCIT). The study recruited 69 stroke patients who received 3 weeks of dCIT for 2 hours daily, 5 days a week. The self-reported outcome measures for daily function were the Motor Activity Log (MAL) including the amount of use (AOU) and quality of movement (QOM), Nottingham Extended Activities of Daily Living Questionnaire (NEADL), and the Stroke Impact Scale (SIS). Age, sex, onset, side of stroke, Fugl-Meyer assessment (FMA), Wolf Motor Function Test (WMFT), and Action Research Arm Test (ARAT) were the potential predictors. The ARAT grasp-grip-pinch score was the most dominant predictor for MAL-AOU and NEADL (P< 0.05), and the ARAT total score for the subscore of the ADL/instrumental ADL section of the SIS (P< 0.05). The FMA wrist-hand score was a significant predictor for MAL-QOM (P< 0.05). Age was the only demographic factor that significantly predicted NEADL performance (P< 0.05). Among the 3 commonly used measures of motor function after stroke, ARAT was the strongest determinant in predicting MAL-AOU, MAL-QOM, and SIS-ADL/instrumental ADL after dCIT.

Predictive factors of functional capacity and real-world functioning in patients with schizophrenia.

PubMed

Menendez-Miranda, I; Garcia-Portilla, M P; Garcia-Alvarez, L; Arrojo, M; Sanchez, P; Sarramea, F; Gomar, J; Bobes-Bascaran, M T; Sierra, P; Saiz, P A; Bobes, J

2015-07-01

This study was performed to identify the predictive factors of functional capacity assessed by the Spanish University of California Performance Skills Assessment (Sp-UPSA) and real-world functioning assessed by the Spanish Personal and Social Performance scale (PSP) in outpatients with schizophrenia. Naturalistic, 6-month follow-up, multicentre, validation study. Here, we report data on 139 patients with schizophrenia at their baseline visit. Positive and Negative Syndrome Scale (PANSS), Clinical Global Impression-Severity (CGI-S), Sp-UPSA and PSP. Pearson's correlation coefficient (r) was used to determine the relationships between variables, and multivariable stepwise linear regression analyses to identify predictive variables of Sp-UPSA and PSP total scores. Functional capacity: scores on the PSP and PANSS-GP entered first and second at P<0.0001 and accounted for 21% of variance (R(2)=0.208, model df=2, F=15.724, P<0.0001). Real-world functioning: scores on the CGI-S (B=-5.406), PANSS-N (B=-0.657) and Sp-UPSA (B=0.230) entered first, second and third, and accounted for 51% of variance (model df=3, F=37.741, P<0.0001). In patients with schizophrenia, functional capacity and real-world functioning are two related but different constructs. Each one predicts the other along with other factors; general psychopathology for functional capacity, and severity of the illness and negative symptoms for real-world functioning. These findings have important clinical implications: (1) both types of functioning should be assessed in patients with schizophrenia and (2) strategies for improving them should be different. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Functional Task Test: 2. Spaceflight-Induced Cardiovascular Change and Recovery During NASA's Functional Task Test

NASA Technical Reports Server (NTRS)

Phillips, Tiffany; Arzeno, Natalia M.; Stenger, Michael; Lee, Stuart M. C.; Bloomberg, Jacob J.; Platts, Steven H.

2011-01-01

The overall objective of the functional task test (FTT) is to correlate spaceflight-induced physiological adaptations with changes in performance of high priority exploration mission-critical tasks. This presentation will focus on the recovery from fall/stand test (RFST), which measures the cardiovascular response to the transition from the prone posture (simulated fall) to standing in normal gravity, as well as heart rate (HR) during 11 functional tasks. As such, this test describes some aspects of spaceflight-induced cardiovascular deconditioning and the course of recovery in Space Shuttle and International Space Station (ISS) astronauts. The sensorimotor and neuromuscular components of the FTT are described in two separate abstracts: Functional Task Test 1 and 3.

Testing the hypothesis of hierarchical predictability in ecological restoration and succession.

PubMed

Abella, Scott R; Schetter, Timothy A; Walters, Timothy L

2018-02-01

To advance predictive ecology, the hypothesis of hierarchical predictability proposes that community measures for which species are interchangeable (e.g., structure and species richness) are more predictable than measures for which species identity matters (e.g., community composition). Predictability is hypothesized to decrease for response measures in order of the following categories: structure, species richness, function, and species composition. We tested this hypothesis using a 14-year, oak savanna-prairie restoration experiment that removed non-native pine plantations at 24 sites in northwestern Ohio, USA. Based on 24 response measures, the data showed minimal support for the hypothesis, because response measures varied in predictability within categories. Half of response measures had over half their variability modeled using fixed (restoration treatment and year) and random plot effects, and these "predictable" measures occurred in all four categories. Pine basal area, environment (e.g., soil texture), and antecedent vegetation accounted for over half the variation in change within the first three post-restoration years for 77% of response measures. Change between the 3rd and 14th years was less predictable, but most restoration measures increased favorably via sites achieving them in unique ways. We propose that variation will not conform with the hypothesis of hierarchical predictability in ecosystems with vegetation dynamics driven by stochastic processes such as seed dispersal, or where vegetation structure and species richness are influenced by species composition. The ability to predict a community measure may be more driven by the number of combinations of casual factors affecting a measure than by the number of values it can have.

Testing prediction methods: Earthquake clustering versus the Poisson model

USGS Publications Warehouse

Michael, A.J.

1997-01-01

Testing earthquake prediction methods requires statistical techniques that compare observed success to random chance. One technique is to produce simulated earthquake catalogs and measure the relative success of predicting real and simulated earthquakes. The accuracy of these tests depends on the validity of the statistical model used to simulate the earthquakes. This study tests the effect of clustering in the statistical earthquake model on the results. Three simulation models were used to produce significance levels for a VLF earthquake prediction method. As the degree of simulated clustering increases, the statistical significance drops. Hence, the use of a seismicity model with insufficient clustering can lead to overly optimistic results. A successful method must pass the statistical tests with a model that fully replicates the observed clustering. However, a method can be rejected based on tests with a model that contains insufficient clustering. U.S. copyright. Published in 1997 by the American Geophysical Union.

Functional Performances on Admission Predict In-Hospital Falls, Injurious Falls, and Fractures in Older Patients: A Prospective Study.

PubMed

Hars, Mélany; Audet, Marie-Claude; Herrmann, François; De Chassey, Jean; Rizzoli, René; Reny, Jean-Luc; Gold, Gabriel; Ferrari, Serge; Trombetti, Andrea

2018-05-01

Falls are common among older inpatients and remain a great challenge for hospitals. Despite the relevance of physical impairments to falls, the prognostic value of performance-based functional measures for in-hospital falls and injurious falls remains unknown. This study aimed to determine the predictive ability and accuracy of various functional tests administered at or close to admission in a geriatric hospital to identify in-hospital fallers and injurious fallers. In this prospective study, conducted in a geriatric hospital in Geneva, Switzerland, 807 inpatients (mean age 85.0 years) were subjected to a battery of functional tests administered by physiotherapists within 3 days (interquartile range 1 to 6) of admission, including Short Physical Performance Battery (SPPB), simplified Tinetti, and Timed Up and Go tests. Patients were prospectively followed up for falls and injurious falls until discharge using mandatory standardized incident report forms and electronic patients' records. During a median length of hospital stay of 23 days (interquartile range 14 to 36), 329 falls occurred in 189 (23.4%) patients, including 161 injurious falls of which 24 were serious. In-hospital fallers displayed significantly poorer functional performances at admission on all tests compared with non-fallers (p < 0.001 for all). In multivariate analysis controlling for age, sex, previous falls, and fall as cause of admission, poorer functional performances on all functional tests predicted in-hospital falls and injurious falls (p < 0.001 for all). The SPPB only significantly predicted serious injurious falls (adjusted odds ratio [OR] = 0.76; 95% confidence interval [CI] 0.60-0.96) and fractures (adjusted OR = 0.76; 95% CI 0.59-0.98). In conclusion, poor functional performances, as assessed by SPPB, are independent predictors of in-hospital falls, injurious falls, and fractures in patients admitted to a geriatric hospital. These findings should help to design

Orion Pad Abort 1 Flight Test: Simulation Predictions Versus Flight Data

NASA Technical Reports Server (NTRS)

Stillwater, Ryan Allanque; Merritt, Deborah S.

2011-01-01

The presentation covers the pre-flight simulation predictions of the Orion Pad Abort 1. The pre-flight simulation predictions are compared to the Orion Pad Abort 1 flight test data. Finally the flight test data is compared to the updated simulation predictions, which show a ove rall improvement in the accuracy of the simulation predictions.

Prediction of liver disease in patients whose liver function tests have been checked in primary care: model development and validation using population-based observational cohorts.

PubMed

McLernon, David J; Donnan, Peter T; Sullivan, Frank M; Roderick, Paul; Rosenberg, William M; Ryder, Steve D; Dillon, John F

2014-06-02

To derive and validate a clinical prediction model to estimate the risk of liver disease diagnosis following liver function tests (LFTs) and to convert the model to a simplified scoring tool for use in primary care. Population-based observational cohort study of patients in Tayside Scotland identified as having their LFTs performed in primary care and followed for 2 years. Biochemistry data were linked to secondary care, prescriptions and mortality data to ascertain baseline characteristics of the derivation cohort. A separate validation cohort was obtained from 19 general practices across the rest of Scotland to externally validate the final model. Primary care, Tayside, Scotland. Derivation cohort: LFT results from 310 511 patients. After exclusions (including: patients under 16 years, patients having initial LFTs measured in secondary care, bilirubin >35 μmol/L, liver complications within 6 weeks and history of a liver condition), the derivation cohort contained 95 977 patients with no clinically apparent liver condition. Validation cohort: after exclusions, this cohort contained 11 653 patients. Diagnosis of a liver condition within 2 years. From the derivation cohort (n=95 977), 481 (0.5%) were diagnosed with a liver disease. The model showed good discrimination (C-statistic=0.78). Given the low prevalence of liver disease, the negative predictive values were high. Positive predictive values were low but rose to 20-30% for high-risk patients. This study successfully developed and validated a clinical prediction model and subsequent scoring tool, the Algorithm for Liver Function Investigations (ALFI), which can predict liver disease risk in patients with no clinically obvious liver disease who had their initial LFTs taken in primary care. ALFI can help general practitioners focus referral on a small subset of patients with higher predicted risk while continuing to address modifiable liver disease risk factors in those at lower risk. Published

Volumetric brain magnetic resonance imaging predicts functioning in bipolar disorder: A machine learning approach.

PubMed

Sartori, Juliana M; Reckziegel, Ramiro; Passos, Ives Cavalcante; Czepielewski, Leticia S; Fijtman, Adam; Sodré, Leonardo A; Massuda, Raffael; Goi, Pedro D; Vianna-Sulzbach, Miréia; Cardoso, Taiane de Azevedo; Kapczinski, Flávio; Mwangi, Benson; Gama, Clarissa S

2018-08-01

Neuroimaging studies have been steadily explored in Bipolar Disorder (BD) in the last decades. Neuroanatomical changes tend to be more pronounced in patients with repeated episodes. Although the role of such changes in cognition and memory is well established, daily-life functioning impairments bulge among the consequences of the proposed progression. The objective of this study was to analyze MRI volumetric modifications in BD and healthy controls (HC) as possible predictors of daily-life functioning through a machine learning approach. Ninety-four participants (35 DSM-IV BD type I and 59 HC) underwent clinical and functioning assessments, and structural MRI. Functioning was assessed using the Functioning Assessment Short Test (FAST). The machine learning analysis was used to identify possible candidates of regional brain volumes that could predict functioning status, through a support vector regression algorithm. Patients with BD and HC did not differ in age, education and marital status. There were significant differences between groups in gender, BMI, FAST score, and employment status. There was significant correlation between observed and predicted FAST score for patients with BD, but not for controls. According to the model, the brain structures volumes that could predict FAST scores were: left superior frontal cortex, left rostral medial frontal cortex, right white matter total volume and right lateral ventricle volume. The machine learning approach demonstrated that brain volume changes in MRI were predictors of FAST score in patients with BD and could identify specific brain areas related to functioning impairment. Copyright © 2018 Elsevier Ltd. All rights reserved.

Executive Function and Personality Predict Instrumental Activities of Daily Living in Alzheimer Disease.

PubMed

Roy, Shumita; Ficarro, Stephanie; Duberstein, Paul; Chapman, Benjamin P; Dubovsky, Steven; Paroski, Margaret; Szigeti, Kinga; Benedict, Ralph H B

2016-11-01

Previous research shows that executive function (EF) and personality independently predict functional decline. Our objective was to determine whether personality traits predict independence with instrumental activities of daily living (IADLs), after accounting for executive dysfunction, in a mixed sample of patients with amnestic mild cognitive impairment (MCI) and Alzheimer disease (AD). In a cross-sectional analysis at a university medical center, 63 healthy older adults (median age: 67.6 years; 71% women) and 119 patients (median age: 75.0 years; 58% women) with varying degrees of AD (probable AD: 85; possible AD: 3; amnestic MCI: 31) were studied. Standardized neuropsychological measures, NEO Five-Factor Inventory (NEO-FFI), and informant-report Lawton and Brody IADL scales were used. All participants underwent neuropsychological evaluation, including administration of self- and informant-report NEO-FFI. Patients additionally underwent neurologic examination, and their informants completed the Lawton and Brody IADL scale. When testing the association between EF and personality on IADLs in the patient sample, conceptual card sorting, informant-report Openness, and informant-report Conscientiousness all significantly predicted IADLs, after accounting for age, education, and depression. In addition, a significant interaction showed that low Conscientiousness and executive dysfunction, in combination, can predict impairment of IADLs. Personality has a unique association with IADLs in patients with AD pathology that is not explained by EF. The findings confirm prior speculation that personality, in addition to cognitive dysfunction, is a risk factor for functional decline. Early identification of vulnerable individuals may allow for intervention to prolong functional independence. Copyright © 2016 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

Transient excitation and mechanical admittance test techniques for prediction of payload vibration environments

NASA Technical Reports Server (NTRS)

Kana, D. D.; Vargas, L. M.

1977-01-01

Transient excitation forces were applied separately to simple beam-and-mass launch vehicle and payload models to develop complex admittance functions for the interface and other appropriate points on the structures. These measured admittances were then analytically combined by a matrix representation to obtain a description of the coupled system dynamic characteristics. Response of the payload model to excitation of the launch vehicle model was predicted and compared with results measured on the combined models. These results are also compared with results of earlier work in which a similar procedure was employed except that steady-state sinusoidal excitation techniques were included. It is found that the method employing transient tests produces results that are better overall than the steady state methods. Furthermore, the transient method requires far less time to implement, and provides far better resolution in the data. However, the data acquisition and handling problem is more complex for this method. It is concluded that the transient test and admittance matrix prediction method can be a valuable tool for development of payload vibration tests.

Functional Independence in Late-Life: Maintaining Physical Functioning in Older Adulthood Predicts Daily Life Function after Age 80

PubMed Central

Leng, Xiaoyan; La Monte, Michael J.; Tindle, Hilary A.; Cochrane, Barbara B.; Shumaker, Sally A.

2016-01-01

Abstract Background. We examined physical functioning (PF) trajectories (maintaining, slowly declining, and rapidly declining) spanning 15 years in older women aged 65–80 and protective factors that predicted better current levels and less decline in functional independence outcomes after age 80. Methods. Women’s Health Initiative extension participants who met criteria (enrolled in either the clinical trial or observational study cohort, >80 years at the data release cutoff, PF survey data from initial enrollment to age 80, and functional independence survey data after age 80) were included in these analyses (mean [ SD ] age = 84.0 [1.4] years; N = 10,478). PF was measured with the SF-36 (mean = 4.9 occasions). Functional independence was measured by self-reported level of dependence in basic and instrumental activities of daily living (ADLs and IADLs) (mean = 3.4 and 3.3 occasions). Results. Maintaining consistent PF in older adulthood extends functional independence in ADL and IADL in late-life. Protective factors shared by ADL and IADL include maintaining PF over time, self-reported excellent or very good health, no history of hip fracture after age 55, and no history of cardiovascular disease. Better IADL function is uniquely predicted by a body mass index less than 25 and no depression. Less ADL and IADL decline is predicted by better self-reported health, and less IADL decline is uniquely predicted by having no history of hip fracture after age 55. Conclusions. Maintaining or improving PF and preventing injury and disease in older adulthood (ages 65–80) has far-reaching implications for improving late-life (after age 80) functional independence. PMID:26858328

Preschool Executive Functioning Abilities Predict Early Mathematics Achievement

ERIC Educational Resources Information Center

Clark, Caron A. C.; Pritchard, Verena E.; Woodward, Lianne J.

2010-01-01

Impairments in executive function have been documented in school-age children with mathematical learning difficulties. However, the utility and specificity of preschool executive function abilities in predicting later mathematical achievement are poorly understood. This study examined linkages between children's developing executive function…

Predicting hydrologic function with the streamwater mircobiome

NASA Astrophysics Data System (ADS)

Good, S. P.; URycki, D. R.; Crump, B. C.

2017-12-01

Recent advances in microbiology allow for rapid and cost-effective determination of the presence of a nearly limitless number of bacterial (and other) species within a water sample. Here, we posit that the quasi-unique taxonomic composition of the aquatic microbiome is an emergent property of a catchment that contains information about hydrologic function at multiple temporal and spatial scales, and term this approach `genohydrolgy.' As first a genohydrology case study, we show that the relative abundance of bacterial species within different operational taxonomic units (OTUs) from six large arctic rivers can be used to predict river discharge at monthly and longer timescales. Using only OTU abundance information and a machine-learning algorithm trained on OTU and discharge data from the other five rivers, our genohydrology approach is able to predict mean monthly discharge values throughout the year with an average Nash-Sutcliffe efficiency (NSE) of 0.50, while the recurrence interval of extreme flows at longer times scales in these rivers was predicted with an NSE of 0.04. This approach demonstrates considerable improvement over prediction of these quantities in each river based only on discharge data from the other five (our null hypothesis), which had average NSE values of -1.19 and -5.50 for the seasonal and recurrence interval discharge values, respectively. Overall the genohydrology approach demonstrates that bacterial diversity within the aquatic microbiome is a large and underutilized data resource with benefits for prediction of hydrologic function.

Quality of Education Predicts Performance on the Wide Range Achievement Test-4th Edition Word Reading Subtest

PubMed Central

Sayegh, Philip; Arentoft, Alyssa; Thaler, Nicholas S.; Dean, Andy C.; Thames, April D.

2014-01-01

The current study examined whether self-rated education quality predicts Wide Range Achievement Test-4th Edition (WRAT-4) Word Reading subtest and neurocognitive performance, and aimed to establish this subtest's construct validity as an educational quality measure. In a community-based adult sample (N = 106), we tested whether education quality both increased the prediction of Word Reading scores beyond demographic variables and predicted global neurocognitive functioning after adjusting for WRAT-4. As expected, race/ethnicity and education predicted WRAT-4 reading performance. Hierarchical regression revealed that when including education quality, the amount of WRAT-4's explained variance increased significantly, with race/ethnicity and both education quality and years as significant predictors. Finally, WRAT-4 scores, but not education quality, predicted neurocognitive performance. Results support WRAT-4 Word Reading as a valid proxy measure for education quality and a key predictor of neurocognitive performance. Future research should examine these findings in larger, more diverse samples to determine their robust nature. PMID:25404004

Predictive Service Life Tests for Roofing Membranes

NASA Astrophysics Data System (ADS)

Bailey, David M.; Cash, Carl G.; Davies, Arthur G.

2002-09-01

The average service life of roofing membranes used in low-slope applications on U.S. Army buildings is estimated to be considerably shorter than the industry-presumed 20-year design life, even when installers carefully adhere to the latest guide specifications. This problem is due in large part to market-driven product development cycles, which do not include time for long-term field testing. To reduce delivery costs, contractors may provide untested, interior membranes in place of ones proven satisfactory in long-term service. Federal procurement regulations require that roofing systems and components be selected according to desired properties and generic type, not brand name. The problem is that a material certified to have satisfactory properties at installation time will not necessarily retain those properties in service. The overall objective of this research is to develop a testing program that can be executed in a matter of weeks to adequately predict a membrane's long-term performance in service. This report details accelerated aging tests of 12 popular membrane materials in the laboratory, and describes outdoor experiment stations set up for long-term exposure tests of those same membranes. The laboratory results will later be correlated with the outdoor test results to develop performance models and predictive service life tests.

Predicting functional recovery after acute ankle sprain.

PubMed

O'Connor, Sean R; Bleakley, Chris M; Tully, Mark A; McDonough, Suzanne M

2013-01-01

Ankle sprains are among the most common acute musculoskeletal conditions presenting to primary care. Their clinical course is variable but there are limited recommendations on prognostic factors. Our primary aim was to identify clinical predictors of short and medium term functional recovery after ankle sprain. A secondary analysis of data from adult participants (N = 85) with an acute ankle sprain, enrolled in a randomized controlled trial was undertaken. The predictive value of variables (age, BMI, gender, injury mechanism, previous injury, weight-bearing status, medial joint line pain, pain during weight-bearing dorsiflexion and lateral hop test) recorded at baseline and at 4 weeks post injury were investigated for their prognostic ability. Recovery was determined from measures of subjective ankle function at short (4 weeks) and medium term (4 months) follow ups. Multivariate stepwise linear regression analyses were undertaken to evaluate the association between the aforementioned variables and functional recovery. Greater age, greater injury grade and weight-bearing status at baseline were associated with lower function at 4 weeks post injury (p<0.01; adjusted R square=0.34). Greater age, weight-bearing status at baseline and non-inversion injury mechanisms were associated with lower function at 4 months (p<0.01; adjusted R square=0.20). Pain on medial palpation and pain on dorsiflexion at 4 weeks were the most valuable prognostic indicators of function at 4 months (p< 0.01; adjusted R square=0.49). The results of the present study provide further evidence that ankle sprains have a variable clinical course. Age, injury grade, mechanism and weight-bearing status at baseline provide some prognostic information for short and medium term recovery. Clinical assessment variables at 4 weeks were the strongest predictors of recovery, explaining 50% of the variance in ankle function at 4 months. Further prospective research is required to highlight the factors that best

The six-minute walk test is an excellent predictor of functional ambulation after total knee arthroplasty

PubMed Central

2013-01-01

Background The Six-minute walk (6MW) and Timed-Up-and-Go (TUG) are short walk tests commonly used to evaluate functional recovery after total knee arthroplasty (TKA). However, little is known about walking capacity of TKA recipients over extended periods typical of everyday living and whether these short walk tests actually predict longer, more functional distances. Further, short walk tests only correlate moderately with patient-reported outcomes. The overarching aims of this study were to compare the performance of TKA recipients in an extended walk test to healthy age-matched controls and to determine the utility of this extended walk test as a research tool to evaluate longer term functional mobility in TKA recipients. Methods The mobility of 32 TKA recipients one year post-surgery and 43 healthy age-matched controls were assessed using the TUG, 6MW and 30-minute walk (30MW) tests. The latter test was repeated one week later. Self-reported function was measured using the WOMAC Index and a physical activity questionnaire. Results 30MW distance was significantly shorter amongst TKA recipients (mean 2108 m [95% CI 1837 to 2381 m]; Controls 3086 m [2981 to 3191 m], P < 0.001). Test-retest repeatability was high (ICC = 0.97, TKA; 0.96, Controls). Amongst TKA recipients, the 30MW distance correlated strongly with the shorter tests (6MW, r = 0.97, P < 0.001; TUG, r = −0.82, P < 0.001). Multiple regression modeling found 6MW distance to be the only significant predictor (P < 0.001) of 30MW distance, explaining 96% of the variability. The TUG test models were moderate predictors of WOMAC function (55%) and physical activity (36%) and were stronger predictors than 6MW and 30 MW tests. Conclusions Though TKA recipients are able to walk for 30 minutes one year post-surgery, their performance falls significantly short of age-matched norms. The 30MW test is strongly predicted by 6MW test performance, thus providing strong construct validity for the use of the 6MW test in

Predicting effects of climate change on the composition and function of soil microbial communities

NASA Astrophysics Data System (ADS)

Dubinsky, E.; Brodie, E.; Myint, C.; Ackerly, D.; van Nostrand, J.; Bird, J.; Zhou, J.; Andersen, G.; Firestone, M.

2008-12-01

Complex soil microbial communities regulate critical ecosystem processes that will be altered by climate change. A critical step towards predicting the impacts of climate change on terrestrial ecosystems is to determine the primary controllers of soil microbial community composition and function, and subsequently evaluate climate change scenarios that alter these controllers. We surveyed complex soil bacterial and archaeal communities across a range of climatic and edaphic conditions to identify critical controllers of soil microbial community composition in the field and then tested the resulting predictions using a 2-year manipulation of precipitation and temperature using mesocosms of California annual grasslands. Community DNA extracted from field soils sampled from six different ecosystems was assayed for bacterial and archaeal communities using high-density phylogenetic microarrays as well as functional gene arrays. Correlations among the relative abundances of thousands of microbial taxa and edaphic factors such as soil moisture and nutrient content provided a basis for predicting community responses to changing soil conditions. Communities of soil bacteria and archaea were strongly structured by single environmental predictors, particularly variables related to soil water. Bacteria in the Actinomycetales and Bacilli consistently demonstrated a strong negative response to increasing soil moisture, while taxa in a greater variety of lineages responded positively to increasing soil moisture. In the climate change experiment, overall bacterial community structure was impacted significantly by total precipitation but not by plant species. Changes in soil moisture due to decreased rainfall resulted in significant and predictable alterations in community structure. Over 70% of the bacterial taxa in common with the cross-ecosystem study responded as predicted to altered precipitation, with the most conserved response from Actinobacteria. The functional consequences

The Development of MST Test Information for the Prediction of Test Performances

ERIC Educational Resources Information Center

Park, Ryoungsun; Kim, Jiseon; Chung, Hyewon; Dodd, Barbara G.

2017-01-01

The current study proposes novel methods to predict multistage testing (MST) performance without conducting simulations. This method, called MST test information, is based on analytic derivation of standard errors of ability estimates across theta levels. We compared standard errors derived analytically to the simulation results to demonstrate the…

Predicting Treatment Response in Social Anxiety Disorder From Functional Magnetic Resonance Imaging

PubMed Central

Doehrmann, Oliver; Ghosh, Satrajit S.; Polli, Frida E.; Reynolds, Gretchen O.; Horn, Franziska; Keshavan, Anisha; Triantafyllou, Christina; Saygin, Zeynep M.; Whitfield-Gabrieli, Susan; Hofmann, Stefan G.; Pollack, Mark; Gabrieli, John D.

2013-01-01

Context Current behavioral measures poorly predict treatment outcome in social anxiety disorder (SAD). To our knowledge, this is the first study to examine neuroimaging-based treatment prediction in SAD. Objective To measure brain activation in patients with SAD as a biomarker to predict subsequent response to cognitive behavioral therapy (CBT). Design Functional magnetic resonance imaging (fMRI) data were collected prior to CBT intervention. Changes in clinical status were regressed on brain responses and tested for selectivity for social stimuli. Setting Patients were treated with protocol-based CBT at anxiety disorder programs at Boston University or Massachusetts General Hospital and underwent neuroimaging data collection at Massachusetts Institute of Technology. Patients Thirty-nine medication-free patients meeting DSM-IV criteria for the generalized subtype of SAD. Interventions Brain responses to angry vs neutral faces or emotional vs neutral scenes were examined with fMRI prior to initiation of CBT. Main Outcome Measures Whole-brain regression analyses with differential fMRI responses for angry vs neutral faces and changes in Liebowitz Social Anxiety Scale score as the treatment outcome measure. Results Pretreatment responses significantly predicted subsequent treatment outcome of patients selectively for social stimuli and particularly in regions of higher-order visual cortex. Combining the brain measures with information on clinical severity accounted for more than 40% of the variance in treatment response and substantially exceeded predictions based on clinical measures at baseline. Prediction success was unaffected by testing for potential confounding factors such as depression severity at baseline. Conclusions The results suggest that brain imaging can provide biomarkers that substantially improve predictions for the success of cognitive behavioral interventions and more generally suggest that such biomarkers may offer evidence-based, personalized

Liver Function Tests

MedlinePlus

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Influences on the Test-Retest Reliability of Functional Connectivity MRI and its Relationship with Behavioral Utility.

PubMed

Noble, Stephanie; Spann, Marisa N; Tokoglu, Fuyuze; Shen, Xilin; Constable, R Todd; Scheinost, Dustin

2017-11-01

Best practices are currently being developed for the acquisition and processing of resting-state magnetic resonance imaging data used to estimate brain functional organization-or "functional connectivity." Standards have been proposed based on test-retest reliability, but open questions remain. These include how amount of data per subject influences whole-brain reliability, the influence of increasing runs versus sessions, the spatial distribution of reliability, the reliability of multivariate methods, and, crucially, how reliability maps onto prediction of behavior. We collected a dataset of 12 extensively sampled individuals (144 min data each across 2 identically configured scanners) to assess test-retest reliability of whole-brain connectivity within the generalizability theory framework. We used Human Connectome Project data to replicate these analyses and relate reliability to behavioral prediction. Overall, the historical 5-min scan produced poor reliability averaged across connections. Increasing the number of sessions was more beneficial than increasing runs. Reliability was lowest for subcortical connections and highest for within-network cortical connections. Multivariate reliability was greater than univariate. Finally, reliability could not be used to improve prediction; these findings are among the first to underscore this distinction for functional connectivity. A comprehensive understanding of test-retest reliability, including its limitations, supports the development of best practices in the field. © The Author 2017. Published by Oxford University Press.

Prediction of R-curves from small coupon tests

NASA Technical Reports Server (NTRS)

Yeh, J. R.; Bray, G. H.; Bucci, R. J.; Macheret, Y.

1994-01-01

R-curves were predicted for Alclad 2024-T3 and C188-T3 sheet using the results of small-coupon Kahn tear tests in combination with two-dimensional elastic-plastic finite element stress analyses. The predictions were compared to experimental R-curves from 6.3, 16 and 60-inch wide M(T) specimens and good agreement was obtained. The method is an inexpensive alternative to wide panel testing for characterizing the fracture toughness of damage-tolerant sheet alloys. The usefulness of this approach was demonstrated by performing residual strength calculations for a two-bay crack in a representative fuselage structure. C188-T3 was predicted to have a 24 percent higher load carrying capability than 2024-T3 in this application as a result of its superior fracture toughness.

Predicting objective function weights from patient anatomy in prostate IMRT treatment planning

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

Lee, Taewoo, E-mail: taewoo.lee@utoronto.ca; Hammad, Muhannad; Chan, Timothy C. Y.

2013-12-15

Purpose: Intensity-modulated radiation therapy (IMRT) treatment planning typically combines multiple criteria into a single objective function by taking a weighted sum. The authors propose a statistical model that predicts objective function weights from patient anatomy for prostate IMRT treatment planning. This study provides a proof of concept for geometry-driven weight determination. Methods: A previously developed inverse optimization method (IOM) was used to generate optimal objective function weights for 24 patients using their historical treatment plans (i.e., dose distributions). These IOM weights were around 1% for each of the femoral heads, while bladder and rectum weights varied greatly between patients. Amore » regression model was developed to predict a patient's rectum weight using the ratio of the overlap volume of the rectum and bladder with the planning target volume at a 1 cm expansion as the independent variable. The femoral head weights were fixed to 1% each and the bladder weight was calculated as one minus the rectum and femoral head weights. The model was validated using leave-one-out cross validation. Objective values and dose distributions generated through inverse planning using the predicted weights were compared to those generated using the original IOM weights, as well as an average of the IOM weights across all patients. Results: The IOM weight vectors were on average six times closer to the predicted weight vectors than to the average weight vector, usingl{sub 2} distance. Likewise, the bladder and rectum objective values achieved by the predicted weights were more similar to the objective values achieved by the IOM weights. The difference in objective value performance between the predicted and average weights was statistically significant according to a one-sided sign test. For all patients, the difference in rectum V54.3 Gy, rectum V70.0 Gy, bladder V54.3 Gy, and bladder V70.0 Gy values between the dose distributions generated by

Predicting objective function weights from patient anatomy in prostate IMRT treatment planning

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

Lee, Taewoo, E-mail: taewoo.lee@utoronto.ca; Hammad, Muhannad; Chan, Timothy C. Y.

Purpose: Intensity-modulated radiation therapy (IMRT) treatment planning typically combines multiple criteria into a single objective function by taking a weighted sum. The authors propose a statistical model that predicts objective function weights from patient anatomy for prostate IMRT treatment planning. This study provides a proof of concept for geometry-driven weight determination. Methods: A previously developed inverse optimization method (IOM) was used to generate optimal objective function weights for 24 patients using their historical treatment plans (i.e., dose distributions). These IOM weights were around 1% for each of the femoral heads, while bladder and rectum weights varied greatly between patients. Amore » regression model was developed to predict a patient's rectum weight using the ratio of the overlap volume of the rectum and bladder with the planning target volume at a 1 cm expansion as the independent variable. The femoral head weights were fixed to 1% each and the bladder weight was calculated as one minus the rectum and femoral head weights. The model was validated using leave-one-out cross validation. Objective values and dose distributions generated through inverse planning using the predicted weights were compared to those generated using the original IOM weights, as well as an average of the IOM weights across all patients. Results: The IOM weight vectors were on average six times closer to the predicted weight vectors than to the average weight vector, usingl{sub 2} distance. Likewise, the bladder and rectum objective values achieved by the predicted weights were more similar to the objective values achieved by the IOM weights. The difference in objective value performance between the predicted and average weights was statistically significant according to a one-sided sign test. For all patients, the difference in rectum V54.3 Gy, rectum V70.0 Gy, bladder V54.3 Gy, and bladder V70.0 Gy values between the dose distributions generated by

Testing process predictions of models of risky choice: a quantitative model comparison approach

PubMed Central

Pachur, Thorsten; Hertwig, Ralph; Gigerenzer, Gerd; Brandstätter, Eduard

2013-01-01

This article presents a quantitative model comparison contrasting the process predictions of two prominent views on risky choice. One view assumes a trade-off between probabilities and outcomes (or non-linear functions thereof) and the separate evaluation of risky options (expectation models). Another view assumes that risky choice is based on comparative evaluation, limited search, aspiration levels, and the forgoing of trade-offs (heuristic models). We derived quantitative process predictions for a generic expectation model and for a specific heuristic model, namely the priority heuristic (Brandstätter et al., 2006), and tested them in two experiments. The focus was on two key features of the cognitive process: acquisition frequencies (i.e., how frequently individual reasons are looked up) and direction of search (i.e., gamble-wise vs. reason-wise). In Experiment 1, the priority heuristic predicted direction of search better than the expectation model (although neither model predicted the acquisition process perfectly); acquisition frequencies, however, were inconsistent with both models. Additional analyses revealed that these frequencies were primarily a function of what Rubinstein (1988) called “similarity.” In Experiment 2, the quantitative model comparison approach showed that people seemed to rely more on the priority heuristic in difficult problems, but to make more trade-offs in easy problems. This finding suggests that risky choice may be based on a mental toolbox of strategies. PMID:24151472

Functional Independence in Late-Life: Maintaining Physical Functioning in Older Adulthood Predicts Daily Life Function after Age 80.

PubMed

Vaughan, Leslie; Leng, Xiaoyan; La Monte, Michael J; Tindle, Hilary A; Cochrane, Barbara B; Shumaker, Sally A

2016-03-01

We examined physical functioning (PF) trajectories (maintaining, slowly declining, and rapidly declining) spanning 15 years in older women aged 65-80 and protective factors that predicted better current levels and less decline in functional independence outcomes after age 80. Women's Health Initiative extension participants who met criteria (enrolled in either the clinical trial or observational study cohort, >80 years at the data release cutoff, PF survey data from initial enrollment to age 80, and functional independence survey data after age 80) were included in these analyses (mean [SD] age = 84.0 [1.4] years; N = 10,478). PF was measured with the SF-36 (mean = 4.9 occasions). Functional independence was measured by self-reported level of dependence in basic and instrumental activities of daily living (ADLs and IADLs) (mean = 3.4 and 3.3 occasions). Maintaining consistent PF in older adulthood extends functional independence in ADL and IADL in late-life. Protective factors shared by ADL and IADL include maintaining PF over time, self-reported excellent or very good health, no history of hip fracture after age 55, and no history of cardiovascular disease. Better IADL function is uniquely predicted by a body mass index less than 25 and no depression. Less ADL and IADL decline is predicted by better self-reported health, and less IADL decline is uniquely predicted by having no history of hip fracture after age 55. Maintaining or improving PF and preventing injury and disease in older adulthood (ages 65-80) has far-reaching implications for improving late-life (after age 80) functional independence. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Predictability Effects on Durations of Content and Function Words in Conversational English

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

Bell, Alan; Brenier, Jason; Gregory, Michelle L.

Content and function word duration are affected differently by their frequency and predictability. Regression analyses of conversational speech show that content words are shorter when they are more frequent, but function words are not. Repeated content words are shorter, but function words are not. Furthermore, function words have shorter pronunciations, after controlling for frequency and predictability. both content and function words are strongly affected by predictability from the word following them, and only very frequent function words show sensitivity to predictability from the preceding word. The results support the view that content and function words are accessed by different productionmore » mechanisms. We argue that words’ form differences due to frequency or repetition stem from their faster or slower lexical access, mediated by a general mechanism that coordinates the pace of higher-level planning and the execution of the articulatory plan.« less

Changes in event-related potential functional networks predict traumatic brain injury in piglets.

PubMed

Atlan, Lorre S; Lan, Ingrid S; Smith, Colin; Margulies, Susan S

2018-06-01

Traumatic brain injury is a leading cause of cognitive and behavioral deficits in children in the US each year. None of the current diagnostic tools, such as quantitative cognitive and balance tests, have been validated to identify mild traumatic brain injury in infants, adults and animals. In this preliminary study, we report a novel, quantitative tool that has the potential to quickly and reliably diagnose traumatic brain injury and which can track the state of the brain during recovery across multiple ages and species. Using 32 scalp electrodes, we recorded involuntary auditory event-related potentials from 22 awake four-week-old piglets one day before and one, four, and seven days after two different injury types (diffuse and focal) or sham. From these recordings, we generated event-related potential functional networks and assessed whether the patterns of the observed changes in these networks could distinguish brain-injured piglets from non-injured. Piglet brains exhibited significant changes after injury, as evaluated by five network metrics. The injury prediction algorithm developed from our analysis of the changes in the event-related potentials functional networks ultimately produced a tool with 82% predictive accuracy. This novel approach is the first application of auditory event-related potential functional networks to the prediction of traumatic brain injury. The resulting tool is a robust, objective and predictive method that offers promise for detecting mild traumatic brain injury, in particular because collecting event-related potentials data is noninvasive and inexpensive. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Predictive testing for Huntington's disease: relationship with partners after testing.

PubMed

Decruyenaere, M; Evers-Kiebooms, G; Cloostermans, T; Boogaerts, A; Demyttenaere, K; Dom, R; Fryns, J P

2004-01-01

This study focuses on the partner relationship of tested persons, 5 years after their predictive test result for Huntington's disease (HD). We describe changes in marital status, quality of the relationship, and perceived changes in the relationship. Twenty-six carriers, 14 of their partners, 33 non-carriers, and 17 of their partners participated in the study. Qualitative and quantitative methods were used. For the majority of tested persons (about 70%), the marital status was unchanged 5 years post test. Overall, carriers rated the quality of the relationship higher than their partners did and they perceived more positive changes. Qualitative data show that a test result leading to changed roles may induce significant marital distress. Another consequence of the test may be the changes in dynamics in asymptomatic carrier couples. A pre-test discussion of the possible impact of the test result on the relationship should result in a better preparation for and more understanding of the reactions after testing. Counselling after testing should stimulate an open communication between partners with consideration of needs and anxieties of both partners.

Comparison of fecal elastase-1 and pancreatic function testing in children.

PubMed

Wali, Prateek D; Loveridge-Lenza, Beth; He, Zhaoping; Horvath, Karoly

2012-02-01

The fecal pancreatic elastase-1 (FE-1) test is considered a simple, noninvasive, indirect measure of pancreatic function. We aimed to evaluate the performance of the FE-1 test compared with the direct pancreatic function test (PFT) with secretin stimulation in children. Data of 70 children (6 months-17 years of age) who had both FE-1 test and PFT were analyzed. The average FE-1 concentration was 403 ± 142 μg/g. Eleven children had concentrations below 200  μg/g, 23 between 201 to 500 μg/g, and 36 were above 500 μg/g. The average pancreatic elastase activity measured on direct stimulation was 49.1 ± 38.6  μmol · min (-1)· ml(-1) and 11 children had activity below the established cutoff (10.5 μmol · min(-1) · ml(-1)). Among the 11 children with pathologic PFT, 7 had normal FE-1, 4 were in the intermediate range (201-500 μg/g), and none were in the low range (<200 μg/g). Among the 59 children with normal direct PFT 11 (19%) had pathologic (<200 μg/g) and 19 (32%) had intermediate FE-1 tests. Twenty-nine children had both normal FE-1 concentration and normal PFT, giving a negative predictive value of 80%. The correlation between pancreatic elastase activity and FE-1 concentration was poor (r = 0.190). The sensitivity of the FE-1 test was found to be 41.7%, whereas the specificity was 49.2%. The positive predictive value of the FE-1 test was only 14%. The FE-1 test is a simple, noninvasive, indirect method; however, ordering physicians should be aware of its limitations. It can give false-positive results and has low sensitivity in children with mild pancreatic insufficiency without cystic fibrosis and in those with isolated pancreatic enzyme deficiencies.

Does the Value of Dynamic Assessment in Predicting End-of-First-Grade Mathematics Performance Differ as a Function of English Language Proficiency?

PubMed Central

Seethaler, Pamela M.; Fuchs, Lynn S.; Fuchs, Douglas; Compton, Donald L.

2015-01-01

The purpose of this study was to assess the added value of dynamic assessment (DA) beyond more conventional static measures for predicting individual differences in year-end 1st-grade calculation (CA) and word-problem (WP) performance, as a function of limited English proficiency (LEP) status. At the start of 1st grade, students (129 LEP; 163 non-LEP) were assessed on a brief static mathematics test, an extended static mathematics test, static tests of domain-general abilities associated with CAs and WPs (vocabulary; reasoning), and DA. Near end of 1st grade, they were assessed on CA and WP. Regression analyses indicated that the value of the predictor depends on the predicted outcome and LEP status. In predicting CAs, the extended mathematics test and DA uniquely explained variance for LEP children, with stronger predictive value for the extended mathematics test; for non-LEP children, the extended mathematics test was the only significant predictor. However, in predicting WPs, only DA and vocabulary were uniquely predictive for LEP children, with stronger value for DA; for non-LEP children, the extended mathematics test and DA were comparably uniquely predictive. Neither the brief static mathematics test nor reasoning was significant in predicting either outcome. The potential value of a gated screening process, using an extended mathematics assessment to predict CAs and using DA to predict WPs, is discussed. PMID:26523068

Track/train dynamics test report transfer function test. Volume 1: Test

NASA Technical Reports Server (NTRS)

Vigil, R. A.

1975-01-01

A description is presented of the transfer function test performed on an open hopper freight car loaded with 80 tons of coal. Test data and a post-test update of the requirements document and test procedure are presented. Included are a statement of the test objective, a description of the test configurations, test facilities, test methods, data acquisition/reduction operations, and a chronological test summary. An index to the data for the three test configurations (X, Y, and Z-axis tests) is presented along with test sequence, run number, test reference, and input parameters.

The Proteome Folding Project: Proteome-scale prediction of structure and function

PubMed Central

Drew, Kevin; Winters, Patrick; Butterfoss, Glenn L.; Berstis, Viktors; Uplinger, Keith; Armstrong, Jonathan; Riffle, Michael; Schweighofer, Erik; Bovermann, Bill; Goodlett, David R.; Davis, Trisha N.; Shasha, Dennis; Malmström, Lars; Bonneau, Richard

2011-01-01

The incompleteness of proteome structure and function annotation is a critical problem for biologists and, in particular, severely limits interpretation of high-throughput and next-generation experiments. We have developed a proteome annotation pipeline based on structure prediction, where function and structure annotations are generated using an integration of sequence comparison, fold recognition, and grid-computing-enabled de novo structure prediction. We predict protein domain boundaries and three-dimensional (3D) structures for protein domains from 94 genomes (including human, Arabidopsis, rice, mouse, fly, yeast, Escherichia coli, and worm). De novo structure predictions were distributed on a grid of more than 1.5 million CPUs worldwide (World Community Grid). We generated significant numbers of new confident fold annotations (9% of domains that are otherwise unannotated in these genomes). We demonstrate that predicted structures can be combined with annotations from the Gene Ontology database to predict new and more specific molecular functions. PMID:21824995

International Low-Earth-Orbit Spacecraft Materials Test Program Initiated for Better Prediction of Durability and Performance

NASA Technical Reports Server (NTRS)

Rutledge, Sharon K.

1999-01-01

Spacecraft in low Earth orbit (LEO) are subjected to many components of the environment, which can cause them to degrade much more rapidly than intended and greatly shorten their functional life. The atomic oxygen, ultraviolet radiation, and cross contamination present in LEO can affect sensitive surfaces such as thermal control paints, multilayer insulation, solar array surfaces, and optical surfaces. The LEO Spacecraft Materials Test (LEO-SMT) program is being conducted to assess the effects of simulated LEO exposure on current spacecraft materials to increase understanding of LEO degradation processes as well as to enable the prediction of in-space performance and durability. Using ground-based simulation facilities to test the durability of materials currently flying in LEO will allow researchers to compare the degradation evidenced in the ground-based facilities with that evidenced on orbit. This will allow refinement of ground laboratory test systems and the development of algorithms to predict the durability and performance of new materials in LEO from ground test results. Accurate predictions based on ground tests could reduce development costs and increase reliability. The wide variety of national and international materials being tested represent materials being functionally used on spacecraft in LEO. The more varied the types of materials tested, the greater the probability that researchers will develop and validate predictive models for spacecraft long-term performance and durability. Organizations that are currently participating in the program are ITT Research Institute (USA), Lockheed Martin (USA), MAP (France), SOREQ Nuclear Research Center (Israel), TNO Institute of Applied Physics (The Netherlands), and UBE Industries, Ltd. (Japan). These represent some of the major suppliers of thermal control and sensor materials currently flying in LEO. The participants provide materials that are exposed to selected levels of atomic oxygen, vacuum ultraviolet

Prediction of frequency for simulation of asphalt mix fatigue tests using MARS and ANN.

PubMed

Ghanizadeh, Ali Reza; Fakhri, Mansour

2014-01-01

Fatigue life of asphalt mixes in laboratory tests is commonly determined by applying a sinusoidal or haversine waveform with specific frequency. The pavement structure and loading conditions affect the shape and the frequency of tensile response pulses at the bottom of asphalt layer. This paper introduces two methods for predicting the loading frequency in laboratory asphalt fatigue tests for better simulation of field conditions. Five thousand (5000) four-layered pavement sections were analyzed and stress and strain response pulses in both longitudinal and transverse directions was determined. After fitting the haversine function to the response pulses by the concept of equal-energy pulse, the effective length of the response pulses were determined. Two methods including Multivariate Adaptive Regression Splines (MARS) and Artificial Neural Network (ANN) methods were then employed to predict the effective length (i.e., frequency) of tensile stress and strain pulses in longitudinal and transverse directions based on haversine waveform. It is indicated that, under controlled stress and strain modes, both methods (MARS and ANN) are capable of predicting the frequency of loading in HMA fatigue tests with very good accuracy. The accuracy of ANN method is, however, more than MARS method. It is furthermore shown that the results of the present study can be generalized to sinusoidal waveform by a simple equation.

Optimal test selection for prediction uncertainty reduction

DOE PAGES

Mullins, Joshua; Mahadevan, Sankaran; Urbina, Angel

2016-12-02

Economic factors and experimental limitations often lead to sparse and/or imprecise data used for the calibration and validation of computational models. This paper addresses resource allocation for calibration and validation experiments, in order to maximize their effectiveness within given resource constraints. When observation data are used for model calibration, the quality of the inferred parameter descriptions is directly affected by the quality and quantity of the data. This paper characterizes parameter uncertainty within a probabilistic framework, which enables the uncertainty to be systematically reduced with additional data. The validation assessment is also uncertain in the presence of sparse and imprecisemore » data; therefore, this paper proposes an approach for quantifying the resulting validation uncertainty. Since calibration and validation uncertainty affect the prediction of interest, the proposed framework explores the decision of cost versus importance of data in terms of the impact on the prediction uncertainty. Often, calibration and validation tests may be performed for different input scenarios, and this paper shows how the calibration and validation results from different conditions may be integrated into the prediction. Then, a constrained discrete optimization formulation that selects the number of tests of each type (calibration or validation at given input conditions) is proposed. Furthermore, the proposed test selection methodology is demonstrated on a microelectromechanical system (MEMS) example.« less

Patient-Customized Drug Combination Prediction and Testing for T-cell Prolymphocytic Leukemia Patients.

PubMed

He, Liye; Tang, Jing; Andersson, Emma I; Timonen, Sanna; Koschmieder, Steffen; Wennerberg, Krister; Mustjoki, Satu; Aittokallio, Tero

2018-05-01

The molecular pathways that drive cancer progression and treatment resistance are highly redundant and variable between individual patients with the same cancer type. To tackle this complex rewiring of pathway cross-talk, personalized combination treatments targeting multiple cancer growth and survival pathways are required. Here we implemented a computational-experimental drug combination prediction and testing (DCPT) platform for efficient in silico prioritization and ex vivo testing in patient-derived samples to identify customized synergistic combinations for individual cancer patients. DCPT used drug-target interaction networks to traverse the massive combinatorial search spaces among 218 compounds (a total of 23,653 pairwise combinations) and identified cancer-selective synergies by using differential single-compound sensitivity profiles between patient cells and healthy controls, hence reducing the likelihood of toxic combination effects. A polypharmacology-based machine learning modeling and network visualization made use of baseline genomic and molecular profiles to guide patient-specific combination testing and clinical translation phases. Using T-cell prolymphocytic leukemia (T-PLL) as a first case study, we show how the DCPT platform successfully predicted distinct synergistic combinations for each of the three T-PLL patients, each presenting with different resistance patterns and synergy mechanisms. In total, 10 of 24 (42%) of selective combination predictions were experimentally confirmed to show synergy in patient-derived samples ex vivo The identified selective synergies among approved drugs, including tacrolimus and temsirolimus combined with BCL-2 inhibitor venetoclax, may offer novel drug repurposing opportunities for treating T-PLL. Significance: An integrated use of functional drug screening combined with genomic and molecular profiling enables patient-customized prediction and testing of drug combination synergies for T-PLL patients. Cancer

A critical assessment of Mus musculus gene function prediction using integrated genomic evidence

PubMed Central

Peña-Castillo, Lourdes; Tasan, Murat; Myers, Chad L; Lee, Hyunju; Joshi, Trupti; Zhang, Chao; Guan, Yuanfang; Leone, Michele; Pagnani, Andrea; Kim, Wan Kyu; Krumpelman, Chase; Tian, Weidong; Obozinski, Guillaume; Qi, Yanjun; Mostafavi, Sara; Lin, Guan Ning; Berriz, Gabriel F; Gibbons, Francis D; Lanckriet, Gert; Qiu, Jian; Grant, Charles; Barutcuoglu, Zafer; Hill, David P; Warde-Farley, David; Grouios, Chris; Ray, Debajyoti; Blake, Judith A; Deng, Minghua; Jordan, Michael I; Noble, William S; Morris, Quaid; Klein-Seetharaman, Judith; Bar-Joseph, Ziv; Chen, Ting; Sun, Fengzhu; Troyanskaya, Olga G; Marcotte, Edward M; Xu, Dong; Hughes, Timothy R; Roth, Frederick P

2008-01-01

Background: Several years after sequencing the human genome and the mouse genome, much remains to be discovered about the functions of most human and mouse genes. Computational prediction of gene function promises to help focus limited experimental resources on the most likely hypotheses. Several algorithms using diverse genomic data have been applied to this task in model organisms; however, the performance of such approaches in mammals has not yet been evaluated. Results: In this study, a standardized collection of mouse functional genomic data was assembled; nine bioinformatics teams used this data set to independently train classifiers and generate predictions of function, as defined by Gene Ontology (GO) terms, for 21,603 mouse genes; and the best performing submissions were combined in a single set of predictions. We identified strengths and weaknesses of current functional genomic data sets and compared the performance of function prediction algorithms. This analysis inferred functions for 76% of mouse genes, including 5,000 currently uncharacterized genes. At a recall rate of 20%, a unified set of predictions averaged 41% precision, with 26% of GO terms achieving a precision better than 90%. Conclusion: We performed a systematic evaluation of diverse, independently developed computational approaches for predicting gene function from heterogeneous data sources in mammals. The results show that currently available data for mammals allows predictions with both breadth and accuracy. Importantly, many highly novel predictions emerge for the 38% of mouse genes that remain uncharacterized. PMID:18613946

Binomial test statistics using Psi functions

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

Bowman, Kimiko o

2007-01-01

For the negative binomial model (probability generating function (p + 1 - pt){sup -k}) a logarithmic derivative is the Psi function difference {psi}(k + x) - {psi}(k); this and its derivatives lead to a test statistic to decide on the validity of a specified model. The test statistic uses a data base so there exists a comparison available between theory and application. Note that the test function is not dominated by outliers. Applications to (i) Fisher's tick data, (ii) accidents data, (iii) Weldon's dice data are included.

Improvement of cardiovascular risk prediction: time to review current knowledge, debates, and fundamentals on how to assess test characteristics.

PubMed

Romanens, Michel; Ackermann, Franz; Spence, John David; Darioli, Roger; Rodondi, Nicolas; Corti, Roberto; Noll, Georg; Schwenkglenks, Matthias; Pencina, Michael

2010-02-01

Cardiovascular risk assessment might be improved with the addition of emerging, new tests derived from atherosclerosis imaging, laboratory tests or functional tests. This article reviews relative risk, odds ratios, receiver-operating curves, posttest risk calculations based on likelihood ratios, the net reclassification improvement and integrated discrimination. This serves to determine whether a new test has an added clinical value on top of conventional risk testing and how this can be verified statistically. Two clinically meaningful examples serve to illustrate novel approaches. This work serves as a review and basic work for the development of new guidelines on cardiovascular risk prediction, taking into account emerging tests, to be proposed by members of the 'Taskforce on Vascular Risk Prediction' under the auspices of the Working Group 'Swiss Atherosclerosis' of the Swiss Society of Cardiology in the future.

Prediction of Lateral Ankle Sprains in Football Players Based on Clinical Tests and Body Mass Index.

PubMed

Gribble, Phillip A; Terada, Masafumi; Beard, Megan Q; Kosik, Kyle B; Lepley, Adam S; McCann, Ryan S; Pietrosimone, Brian G; Thomas, Abbey C

2016-02-01

The lateral ankle sprain (LAS) is the most common injury suffered in sports, especially in football. While suggested in some studies, a predictive role of clinical tests for LAS has not been established. To determine which clinical tests, focused on potentially modifiable factors of movement patterns and body mass index (BMI), could best demonstrate risk of LAS among high school and collegiate football players. Case-control study; Level of evidence, 3. A total of 539 high school and collegiate football players were evaluated during the preseason with the Star Excursion Balance Test (SEBT) and Functional Movement Screen as well as BMI. Results were compared between players who did and did not suffer an LAS during the season. Logistic regression analyses and calculated odds ratios were used to determine which measures predicted risk of LAS. The LAS group performed worse on the SEBT-anterior reaching direction (SEBT-ANT) and had higher BMI as compared with the noninjured group (P < .001). The strongest prediction models corresponded with the SEBT-ANT. Low performance on the SEBT-ANT predicted a risk of LAS in football players. BMI was also significantly higher in football players who sustained an LAS. Identifying clinical tools for successful LAS injury risk prediction will be a critical step toward the creation of effective prevention programs to reduce risk of sustaining an LAS during participation in football. © 2015 The Author(s).

Predicting human protein function with multi-task deep neural networks.

PubMed

Fa, Rui; Cozzetto, Domenico; Wan, Cen; Jones, David T

2018-01-01

Machine learning methods for protein function prediction are urgently needed, especially now that a substantial fraction of known sequences remains unannotated despite the extensive use of functional assignments based on sequence similarity. One major bottleneck supervised learning faces in protein function prediction is the structured, multi-label nature of the problem, because biological roles are represented by lists of terms from hierarchically organised controlled vocabularies such as the Gene Ontology. In this work, we build on recent developments in the area of deep learning and investigate the usefulness of multi-task deep neural networks (MTDNN), which consist of upstream shared layers upon which are stacked in parallel as many independent modules (additional hidden layers with their own output units) as the number of output GO terms (the tasks). MTDNN learns individual tasks partially using shared representations and partially from task-specific characteristics. When no close homologues with experimentally validated functions can be identified, MTDNN gives more accurate predictions than baseline methods based on annotation frequencies in public databases or homology transfers. More importantly, the results show that MTDNN binary classification accuracy is higher than alternative machine learning-based methods that do not exploit commonalities and differences among prediction tasks. Interestingly, compared with a single-task predictor, the performance improvement is not linearly correlated with the number of tasks in MTDNN, but medium size models provide more improvement in our case. One of advantages of MTDNN is that given a set of features, there is no requirement for MTDNN to have a bootstrap feature selection procedure as what traditional machine learning algorithms do. Overall, the results indicate that the proposed MTDNN algorithm improves the performance of protein function prediction. On the other hand, there is still large room for deep learning

A novel and simple test of gait adaptability predicts gold standard measures of functional mobility in stroke survivors.

PubMed

Hollands, K L; Pelton, T A; van der Veen, S; Alharbi, S; Hollands, M A

2016-01-01

Although there is evidence that stroke survivors have reduced gait adaptability, the underlying mechanisms and the relationship to functional recovery are largely unknown. We explored the relationships between walking adaptability and clinical measures of balance, motor recovery and functional ability in stroke survivors. Stroke survivors (n=42) stepped to targets, on a 6m walkway, placed to elicit step lengthening, shortening and narrowing on paretic and non-paretic sides. The number of targets missed during six walks and target stepping speed was recorded. Fugl-Meyer (FM), Berg Balance Scale (BBS), self-selected walking speed (SWWS) and single support (SS) and step length (SL) symmetry (using GaitRite when not walking to targets) were also assessed. Stepwise multiple-linear regression was used to model the relationships between: total targets missed, number missed with paretic and non-paretic legs, target stepping speed, and each clinical measure. Regression revealed a significant model for each outcome variable that included only one independent variable. Targets missed by the paretic limb, was a significant predictor of FM (F(1,40)=6.54, p=0.014,). Speed of target stepping was a significant predictor of each of BBS (F(1,40)=26.36, p<0.0001), SSWS (F(1,40)=37.00, p<0.0001). No variables were significant predictors of SL or SS asymmetry. Speed of target stepping was significantly predictive of BBS and SSWS and paretic targets missed predicted FM, suggesting that fast target stepping requires good balance and accurate stepping demands good paretic leg function. The relationships between these parameters indicate gait adaptability is a clinically meaningful target for measurement and treatment of functionally adaptive walking ability in stroke survivors. Copyright © 2015 Elsevier B.V. All rights reserved.

Dopamine neurons share common response function for reward prediction error

PubMed Central

Eshel, Neir; Tian, Ju; Bukwich, Michael; Uchida, Naoshige

2016-01-01

Dopamine neurons are thought to signal reward prediction error, or the difference between actual and predicted reward. How dopamine neurons jointly encode this information, however, remains unclear. One possibility is that different neurons specialize in different aspects of prediction error; another is that each neuron calculates prediction error in the same way. We recorded from optogenetically-identified dopamine neurons in the lateral ventral tegmental area (VTA) while mice performed classical conditioning tasks. Our tasks allowed us to determine the full prediction error functions of dopamine neurons and compare them to each other. We found striking homogeneity among individual dopamine neurons: their responses to both unexpected and expected rewards followed the same function, just scaled up or down. As a result, we could describe both individual and population responses using just two parameters. Such uniformity ensures robust information coding, allowing each dopamine neuron to contribute fully to the prediction error signal. PMID:26854803

Developmental Delays in Executive Function from 3 to 5 Years of Age Predict Kindergarten Academic Readiness

ERIC Educational Resources Information Center

Willoughby, Michael T.; Magnus, Brooke; Vernon-Feagans, Lynne; Blair, Clancy B.

2017-01-01

Substantial evidence has established that individual differences in executive function (EF) in early childhood are uniquely predictive of children's academic readiness at school entry. The current study tested whether growth trajectories of EF across the early childhood period could be used to identify a subset of children who were at pronounced…

Use of Preoperative Functional MRI to Predict Verbal Memory Decline After Temporal Lobe Epilepsy Surgery

PubMed Central

Binder, Jeffrey R.; Sabsevitz, David S.; Swanson, Sara J.; Hammeke, Thomas A.; Raghavan, Manoj; Mueller, Wade M.

2010-01-01

Purpose Verbal memory decline is a frequent complication of left anterior temporal lobectomy (L-ATL). The goal of this study was to determine whether preoperative language mapping using functional magnetic resonance imaging (fMRI) is useful for predicting which patients are likely to experience verbal memory decline after L-ATL. Methods Sixty L-ATL patients underwent preoperative language mapping with fMRI, preoperative intracarotid amobarbital (Wada) testing for language and memory lateralization, and pre- and postoperative neuropsychological testing. Demographic, historical, neuropsychological, and imaging variables were examined for their ability to predict pre- to postoperative memory change. Results Verbal memory decline occurred in over 30% of patients. Good preoperative performance, late age at onset of epilepsy, left dominance on fMRI, and left dominance on the Wada test were each predictive of memory decline. Preoperative performance and age at onset together accounted for roughly 50% of the variance in memory outcome (p < .001), and fMRI explained an additional 10% of this variance (p ≤ .003). Neither Wada memory asymmetry nor Wada language asymmetry added additional predictive power beyond these noninvasive measures. Discussion Preoperative fMRI is useful for identifying patients at high risk for verbal memory decline prior to L-ATL surgery. Lateralization of language is correlated with lateralization of verbal memory, whereas Wada memory testing is either insufficiently reliable or insufficiently material-specific to accurately localize verbal memory processes. PMID:18435753

Concomitant prediction of function and fold at the domain level with GO-based profiles.

PubMed

Lopez, Daniel; Pazos, Florencio

2013-01-01

Predicting the function of newly sequenced proteins is crucial due to the pace at which these raw sequences are being obtained. Almost all resources for predicting protein function assign functional terms to whole chains, and do not distinguish which particular domain is responsible for the allocated function. This is not a limitation of the methodologies themselves but it is due to the fact that in the databases of functional annotations these methods use for transferring functional terms to new proteins, these annotations are done on a whole-chain basis. Nevertheless, domains are the basic evolutionary and often functional units of proteins. In many cases, the domains of a protein chain have distinct molecular functions, independent from each other. For that reason resources with functional annotations at the domain level, as well as methodologies for predicting function for individual domains adapted to these resources are required.We present a methodology for predicting the molecular function of individual domains, based on a previously developed database of functional annotations at the domain level. The approach, which we show outperforms a standard method based on sequence searches in assigning function, concomitantly predicts the structural fold of the domains and can give hints on the functionally important residues associated to the predicted function.

Evaluation of Short-Term Bioassays to Predict Functional Impairment. Development of Hepatic Bioassays in Laboratory Animals, Directory of Institutions/Individuals.

DTIC Science & Technology

1980-10-01

Organizations Compounds Tested Morphological Tests Toxic Substances Functional Tests rR ACT Cutlue OM v.a e sif nemooery ad Identify by block number) %MITRE has...demonstrated ability to evaluate and predict hepatic impairment rvsulting from toxicant exposures. This directory is a companion to Selected Short-Term...Hepatic Toxicity Tests, which describes the available hepatic testing protocols and assesses their suitability for a screening program. This direc

The Role of Predictability in Saccadic Eye Responses in the Suppression Head Impulse Test of Horizontal Semicircular Canal Function.

PubMed

Rey-Martinez, Jorge; Yanes, Joaquin; Esteban, Jonathan; Sanz, Ricardo; Martin-Sanz, Eduardo

2017-01-01

evidence regarding the influence of predictability on the latency of the SHIMP saccadic responses, suggesting that early saccades are probably caused by a conditioned response of the participant. The lack of relationship between the hVOR gain and the latency of the saccades suggests that the predictive behavior that caused the early eye saccades are independent of the vestibular function.

Domains of cognitive function in early old age: which ones are predicted by pre-retirement psychosocial work characteristics?

PubMed Central

Sabbath, Erika; Andel, Ross; Zins, Marie; Goldberg, Marcel; Berr, Claudine

2016-01-01

Background Psychosocial work characteristics may predict cognitive functioning after retirement. However, little research has explored specific cognitive domains associated with psychosocial work environments. Our study tested whether exposure to job demands, job control, and their combination during working life predicted post-retirement performance on eight cognitive tests. Methods We used data from French GAZEL cohort members who had undergone post-retirement cognitive testing (n=2,149). Psychosocial job characteristics were measured on average four years before retirement using Karasek’s Job Content Questionnaire (job demands, job control, demand-control combinations). We tested associations between these exposures and post-retirement performance on tests of executive function, visual-motor speed, psycho-motor speed, verbal memory, and verbal fluency using OLS regression. Results Low job control during working life was negatively associated with executive function, psychomotor speed, phonemic fluency, and semantic fluency after retirement (p’s<.05) even after adjustment for demographics, socioeconomic status, health and social behaviours, and vascular risk factors. Both passive (low-demand, low-control) and high-strain (high-demand, low-control) jobs were associated with lower scores on phonemic and semantic fluency when compared to low-strain (low-demand, high-control) jobs. Conclusions Low job control, in combination with both high and low job demands, is associated with post-retirement deficits in some, but not all, cognitive domains. In addition to work stress, associations between passive work and subsequent cognitive function may implicate lack of cognitive engagement at work as a risk factor for future cognitive difficulties. PMID:27188277

Using OCT to predict post-transplant renal function

NASA Astrophysics Data System (ADS)

Andrews, Peter M.; Chen, Yu; Wierwille, Jeremiah; Joh, Daniel; Alexandrov, Peter; Rogalsky, Derek; Moody, Patrick; Chen, Allen; Cooper, Matthew; Verbesey, Jennifer E.; Gong, Wei; Wang, Hsing-Wen

2013-03-01

The treatment of choice for patients with end-stage renal disease is kidney transplantation. However, acute tubular necrosis (ATN) induced by an ischemic insult (e.g., from prolonged ex vivo storage times, or non-heart beating cadavers) is a major factor limiting the availability of donor kidneys. In addition, ischemic induced ATN is a significant risk factor for eventual graft survival and can be difficult to discern from rejection. Currently, there are no rapid and reliable tests to determine ATN suffered by donor kidneys and whether or not donor kidneys might exhibit delayed graft function. OCT (optical coherence tomography) is a rapidly emerging imaging modality that can function as a type of "optical biopsy", providing cross-sectional images of tissue morphology in situ and in real-time. In a series of recent clinical trials, we evaluated the ability of OCT to image those features of the renal microstructure that are predictive of ATN. Specifically, we found that OCT could effectively image through the intact human renal capsule and determine the extent of acute tubular necrosis. We also found that Doppler based OCT (i.e., DOCT) revealed renal blood flow dynamics that is also reported to be a determiner of post-transplant renal function. This kind of information will allow transplant surgeons to make the most efficient use of available donor kidneys, eliminate the possible use of bad donor kidneys, provide a measure of expected post-transplant renal function, and allow better distinction between post-transplant immunological rejection and ischemic-induced acute renal failure.

Protein function prediction--the power of multiplicity.

PubMed

Rentzsch, Robert; Orengo, Christine A

2009-04-01

Advances in experimental and computational methods have quietly ushered in a new era in protein function annotation. This 'age of multiplicity' is marked by the notion that only the use of multiple tools, multiple evidence and considering the multiple aspects of function can give us the broad picture that 21st century biology will need to link and alter micro- and macroscopic phenotypes. It might also help us to undo past mistakes by removing errors from our databases and prevent us from producing more. On the downside, multiplicity is often confusing. We therefore systematically review methods and resources for automated protein function prediction, looking at individual (biochemical) and contextual (network) functions, respectively.

Sweat testing to evaluate autonomic function

PubMed Central

Illigens, Ben M.W.; Gibbons, Christopher H.

2011-01-01

Sudomotor dysfunction is one of the earliest detectable neurophysiologic abnormalities in distal small fiber neuropathy. Traditional neurophysiologic measurements of sudomotor function include thermoregulatory sweat testing (TST), quantitative sudomotor axon reflex testing (QSART), silicone impressions, the sympathetic skin response (SSR), and the recent addition of quantitative direct and indirect axon reflex testing (QDIRT). These testing techniques, when used in combination, can detect and localized pre- and postganglionic lesions, can provide early diagnosis of sudomotor dysfunction and can monitor disease progression or disease recovery. In this article, we review the common tests available for assessment of sudomotor function, detail the testing methodology, review the limitations and provide examples of test results. PMID:18989618

Prediction of preterm birth in twin gestations using biophysical and biochemical tests

PubMed Central

Conde-Agudelo, Agustin; Romero, Roberto

2018-01-01

The objective of this study was to determine the performance of biophysical and biochemical tests for the prediction of preterm birth in both asymptomatic and symptomatic women with twin gestations. We identified a total of 19 tests proposed to predict preterm birth, mainly in asymptomatic women. In these women, a single measurement of cervical length with transvaginal ultrasound before 25 weeks of gestation appears to be a good test to predict preterm birth. Its clinical potential is enhanced by the evidence that vaginal progesterone administration in asymptomatic women with twin gestations and a short cervix reduces neonatal morbidity and mortality associated with spontaneous preterm delivery. Other tests proposed for the early identification of asymptomatic women at increased risk of preterm birth showed minimal to moderate predictive accuracy. None of the tests evaluated in this review meet the criteria to be considered clinically useful to predict preterm birth among patients with an episode of preterm labor. However, a negative cervicovaginal fetal fibronectin test could be useful in identifying women who are not at risk for delivering within the next week, which could avoid unnecessary hospitalization and treatment. This review underscores the need to develop accurate tests for predicting preterm birth in twin gestations. Moreover, the use of interventions in these patients based on test results should be associated with the improvement of perinatal outcomes. PMID:25072736

Prediction of preterm birth in twin gestations using biophysical and biochemical tests.

PubMed

Conde-Agudelo, Agustin; Romero, Roberto

2014-12-01

The objective of this study was to determine the performance of biophysical and biochemical tests for the prediction of preterm birth in both asymptomatic and symptomatic women with twin gestations. We identified a total of 19 tests proposed to predict preterm birth, mainly in asymptomatic women. In these women, a single measurement of cervical length with transvaginal ultrasound before 25 weeks of gestation appears to be a good test to predict preterm birth. Its clinical potential is enhanced by the evidence that vaginal progesterone administration in asymptomatic women with twin gestations and a short cervix reduces neonatal morbidity and mortality associated with spontaneous preterm delivery. Other tests proposed for the early identification of asymptomatic women at increased risk of preterm birth showed minimal to moderate predictive accuracy. None of the tests evaluated in this review meet the criteria to be considered clinically useful to predict preterm birth among patients with an episode of preterm labor. However, a negative cervicovaginal fetal fibronectin test could be useful in identifying women who are not at risk for delivering within the next week, which could avoid unnecessary hospitalization and treatment. This review underscores the need to develop accurate tests for predicting preterm birth in twin gestations. Moreover, the use of interventions in these patients based on test results should be associated with the improvement of perinatal outcomes. Copyright © 2014. Published by Elsevier Inc.

Structural habitat predicts functional dispersal habitat of a large carnivore: how leopards change spots.

PubMed

Fattebert, Julien; Robinson, Hugh S; Balme, Guy; Slotow, Rob; Hunter, Luke

2015-10-01

Natal dispersal promotes inter-population linkage, and is key to spatial distribution of populations. Degradation of suitable landscape structures beyond the specific threshold of an individual's ability to disperse can therefore lead to disruption of functional landscape connectivity and impact metapopulation function. Because it ignores behavioral responses of individuals, structural connectivity is easier to assess than functional connectivity and is often used as a surrogate for landscape connectivity modeling. However using structural resource selection models as surrogate for modeling functional connectivity through dispersal could be erroneous. We tested how well a second-order resource selection function (RSF) models (structural connectivity), based on GPS telemetry data from resident adult leopard (Panthera pardus L.), could predict subadult habitat use during dispersal (functional connectivity). We created eight non-exclusive subsets of the subadult data based on differing definitions of dispersal to assess the predictive ability of our adult-based RSF model extrapolated over a broader landscape. Dispersing leopards used habitats in accordance with adult selection patterns, regardless of the definition of dispersal considered. We demonstrate that, for a wide-ranging apex carnivore, functional connectivity through natal dispersal corresponds to structural connectivity as modeled by a second-order RSF. Mapping of the adult-based habitat classes provides direct visualization of the potential linkages between populations, without the need to model paths between a priori starting and destination points. The use of such landscape scale RSFs may provide insight into predicting suitable dispersal habitat peninsulas in human-dominated landscapes where mitigation of human-wildlife conflict should be focused. We recommend the use of second-order RSFs for landscape conservation planning and propose a similar approach to the conservation of other wide-ranging large

Fatigue life prediction of liquid rocket engine combustor with subscale test verification

NASA Astrophysics Data System (ADS)

Sung, In-Kyung

Reusable rocket systems such as the Space Shuttle introduced a new era in propulsion system design for economic feasibility. Practical reusable systems require an order of magnitude increase in life. To achieve this improved methods are needed to assess failure mechanisms and to predict life cycles of rocket combustor. A general goal of the research was to demonstrate the use of subscale rocket combustor prototype in a cost-effective test program. Life limiting factors and metal behaviors under repeated loads were surveyed and reviewed. The life prediction theories are presented, with an emphasis on studies that used subscale test hardware for model validation. From this review, low cycle fatigue (LCF) and creep-fatigue interaction (ratcheting) were identified as the main life limiting factors of the combustor. Several life prediction methods such as conventional and advanced viscoplastic models were used to predict life cycle due to low cycle thermal stress, transient effects, and creep rupture damage. Creep-fatigue interaction and cyclic hardening were also investigated. A prediction method based on 2D beam theory was modified using 3D plate deformation theory to provide an extended prediction method. For experimental validation two small scale annular plug nozzle thrusters were designed, built and tested. The test article was composed of a water-cooled liner, plug annular nozzle and 200 psia precombustor that used decomposed hydrogen peroxide as the oxidizer and JP-8 as the fuel. The first combustor was tested cyclically at the Advanced Propellants and Combustion Laboratory at Purdue University. Testing was stopped after 140 cycles due to an unpredicted failure mechanism due to an increasing hot spot in the location where failure was predicted. A second combustor was designed to avoid the previous failure, however, it was over pressurized and deformed beyond repair during cold-flow test. The test results are discussed and compared to the analytical and numerical

Predicting outcome of Morris water maze test in vascular dementia mouse model with deep learning

PubMed Central

Mogi, Masaki; Iwanami, Jun; Min, Li-Juan; Bai, Hui-Yu; Shan, Bao-Shuai; Kukida, Masayoshi; Kan-no, Harumi; Ikeda, Shuntaro; Higaki, Jitsuo; Horiuchi, Masatsugu

2018-01-01

The Morris water maze test (MWM) is one of the most popular and established behavioral tests to evaluate rodents’ spatial learning ability. The conventional training period is around 5 days, but there is no clear evidence or guidelines about the appropriate duration. In many cases, the final outcome of the MWM seems predicable from previous data and their trend. So, we assumed that if we can predict the final result with high accuracy, the experimental period could be shortened and the burden on testers reduced. An artificial neural network (ANN) is a useful modeling method for datasets that enables us to obtain an accurate mathematical model. Therefore, we constructed an ANN system to estimate the final outcome in MWM from the previously obtained 4 days of data in both normal mice and vascular dementia model mice. Ten-week-old male C57B1/6 mice (wild type, WT) were subjected to bilateral common carotid artery stenosis (WT-BCAS) or sham-operation (WT-sham). At 6 weeks after surgery, we evaluated their cognitive function with MWM. Mean escape latency was significantly longer in WT-BCAS than in WT-sham. All data were collected and used as training data and test data for the ANN system. We defined a multiple layer perceptron (MLP) as a prediction model using an open source framework for deep learning, Chainer. After a certain number of updates, we compared the predicted values and actual measured values with test data. A significant correlation coefficient was derived form the updated ANN model in both WT-sham and WT-BCAS. Next, we analyzed the predictive capability of human testers with the same datasets. There was no significant difference in the prediction accuracy between human testers and ANN models in both WT-sham and WT-BCAS. In conclusion, deep learning method with ANN could predict the final outcome in MWM from 4 days of data with high predictive accuracy in a vascular dementia model. PMID:29415035

Predicting outcome of Morris water maze test in vascular dementia mouse model with deep learning.

PubMed

Higaki, Akinori; Mogi, Masaki; Iwanami, Jun; Min, Li-Juan; Bai, Hui-Yu; Shan, Bao-Shuai; Kukida, Masayoshi; Kan-No, Harumi; Ikeda, Shuntaro; Higaki, Jitsuo; Horiuchi, Masatsugu

2018-01-01

The Morris water maze test (MWM) is one of the most popular and established behavioral tests to evaluate rodents' spatial learning ability. The conventional training period is around 5 days, but there is no clear evidence or guidelines about the appropriate duration. In many cases, the final outcome of the MWM seems predicable from previous data and their trend. So, we assumed that if we can predict the final result with high accuracy, the experimental period could be shortened and the burden on testers reduced. An artificial neural network (ANN) is a useful modeling method for datasets that enables us to obtain an accurate mathematical model. Therefore, we constructed an ANN system to estimate the final outcome in MWM from the previously obtained 4 days of data in both normal mice and vascular dementia model mice. Ten-week-old male C57B1/6 mice (wild type, WT) were subjected to bilateral common carotid artery stenosis (WT-BCAS) or sham-operation (WT-sham). At 6 weeks after surgery, we evaluated their cognitive function with MWM. Mean escape latency was significantly longer in WT-BCAS than in WT-sham. All data were collected and used as training data and test data for the ANN system. We defined a multiple layer perceptron (MLP) as a prediction model using an open source framework for deep learning, Chainer. After a certain number of updates, we compared the predicted values and actual measured values with test data. A significant correlation coefficient was derived form the updated ANN model in both WT-sham and WT-BCAS. Next, we analyzed the predictive capability of human testers with the same datasets. There was no significant difference in the prediction accuracy between human testers and ANN models in both WT-sham and WT-BCAS. In conclusion, deep learning method with ANN could predict the final outcome in MWM from 4 days of data with high predictive accuracy in a vascular dementia model.

Predicting ground level impacts of solid rocket motor testing

NASA Technical Reports Server (NTRS)

Douglas, Willard L.; Eagan, Ellen E.; Kennedy, Carolyn D.; Mccaleb, Rebecca C.

1993-01-01

Beginning in August of 1988 and continuing until the present, NASA at Stennis Space Center, Mississippi has conducted environmental monitoring of selected static test firings of the solid rocket motor used on the Space Shuttle. The purpose of the study was to assess the modeling protocol adapted for use in predicting plume behavior for the Advanced Solid Rocket Motor that is to be tested in Mississippi beginning in the mid-1990's. Both motors use an aluminum/ammonium perchlorate fuel that produces HCl and Al2O3 particulates as the major combustion products of concern. A combination of COMBUS.sr and PRISE.sr subroutines and the INPUFF model are used to predict the centerline stabilization height, the maximum concentration of HCl and Al2O3 at ground level, and distance to maximum concentration. Ground studies were conducted to evaluate the ability of the model to make these predictions. The modeling protocol was found to be conservative in the prediction of plume stabilization height and in the concentrations of the two emission products predicted.

An Influence Function Method for Predicting Store Aerodynamic Characteristics during Weapon Separation,

DTIC Science & Technology

1981-05-14

8217 AO-Ail 777 GRUMMAN AEROSPACE CORP BETHPAGE NY F/G 20/4 AN INFLUENCE FUNCTION METHOD FOR PREDICTING STORE AERODYNAMIC C--ETCCU) MAY 8 1 R MEYER, A...CENKO, S YARDS UNCLASSIFIED N ’.**~~N**n I EHEEKI j~j .25 Q~4 111110 111_L 5. AN INFLUENCE FUNCTION METHOD FOR PREDICTING STORE AERODYNAMIC...extended to their logical conclusion one is led quite naturally to consideration of an " Influence Function Method" for I predicting store aerodynamic

Sensitivity and Specificity of Eustachian Tube Function Tests in Adults

PubMed Central

Doyle, William J.; Swarts, J. Douglas; Banks, Julianne; Casselbrant, Margaretha L; Mandel, Ellen M; Alper, Cuneyt M.

2013-01-01

Objective Determine if Eustachian Tube (ET) function (ETF) tests can identify ears with physician-diagnosed ET dysfunction (ETD) in a mixed population at high sensitivity and specificity and define the inter-relatedness of ETF test parameters. Methods ETF was evaluated using the Forced-Response, Inflation-Deflation, Valsalva and Sniffing tests in 15 control ears of adult subjects after unilateral myringotomy (Group I) and in 23 ears of 19 adult subjects with ventilation tubes inserted for ETD (Group II). Data were analyzed using logistic regression including each parameter independently and then a step-down Discriminant Analysis including all ETF test parameters to predict group assignment. Factor Analysis operating over all parameters was used to explore relatedness. Results The Discriminant Analysis identified 4 ETF test parameters (Valsalva, ET opening pressure, dilatory efficiency and % positive pressure equilibrated) that together correctly assigned ears to Group II at a sensitivity of 95% and a specificity of 83%. Individual parameters representing the efficiency of ET opening during swallowing showed moderately accurate assignments of ears to their respective groups. Three factors captured approximately 98% of the variance among parameters, the first had negative loadings of the ETF structural parameters, the second had positive loadings of the muscle-assisted ET opening parameters and the third had negative loadings of the muscle-assisted ET opening parameters and positive loadings of the structural parameters. Discussion These results show that ETF tests can correctly assign individual ears to physician-diagnosed ETD with high sensitivity and specificity and that ETF test parameters can be grouped into structural-functional categories. PMID:23868429

Aortic stiffness predicts functional outcome in patients after ischemic stroke.

PubMed

Gasecki, Dariusz; Rojek, Agnieszka; Kwarciany, Mariusz; Kubach, Marlena; Boutouyrie, Pierre; Nyka, Walenty; Laurent, Stephane; Narkiewicz, Krzysztof

2012-02-01

Increased aortic stiffness (measured by carotid-femoral pulse wave velocity) and central augmentation index have been shown to independently predict cardiovascular events, including stroke. We studied whether pulse wave velocity and central augmentation index predict functional outcome after ischemic stroke. In a prospective study, we enrolled 99 patients with acute ischemic stroke (age 63.7 ± 12.4 years, admission National Institutes of Health Stroke Scale score 6.6 ± 6.6, mean ± SD). Carotid-femoral pulse wave velocity and central augmentation index (SphygmoCor) were measured 1 week after stroke onset. Functional outcome was evaluated 90 days after stroke using the modified Rankin Scale with modified Rankin Scale score of 0 to 1 considered an excellent outcome. In univariate analysis, low carotid-femoral pulse wave velocity (P=0.000001) and low central augmentation index (P=0.028) were significantly associated with excellent stroke outcome. Age, severity of stroke, presence of previous stroke, diabetes, heart rate, and peripheral pressures also predicted stroke functional outcome. In multivariate analysis, the predictive value of carotid-femoral pulse wave velocity (<9.4 m/s) remained significant (OR, 0.21; 95% CI, 0.06-0.79; P=0.02) after adjustment for age, National Institutes of Health Stroke Scale score on admission, and presence of previous stroke. By contrast, central augmentation index had no significant predictive value after adjustment. This study indicates that aortic stiffness is an independent predictor of functional outcome in patients with acute ischemic stroke.

Life prediction for high temperature low cycle fatigue of two kinds of titanium alloys based on exponential function

NASA Astrophysics Data System (ADS)

Mu, G. Y.; Mi, X. Z.; Wang, F.

2018-01-01

The high temperature low cycle fatigue tests of TC4 titanium alloy and TC11 titanium alloy are carried out under strain controlled. The relationships between cyclic stress-life and strain-life are analyzed. The high temperature low cycle fatigue life prediction model of two kinds of titanium alloys is established by using Manson-Coffin method. The relationship between failure inverse number and plastic strain range presents nonlinear in the double logarithmic coordinates. Manson-Coffin method assumes that they have linear relation. Therefore, there is bound to be a certain prediction error by using the Manson-Coffin method. In order to solve this problem, a new method based on exponential function is proposed. The results show that the fatigue life of the two kinds of titanium alloys can be predicted accurately and effectively by using these two methods. Prediction accuracy is within ±1.83 times scatter zone. The life prediction capability of new methods based on exponential function proves more effective and accurate than Manson-Coffin method for two kinds of titanium alloys. The new method based on exponential function can give better fatigue life prediction results with the smaller standard deviation and scatter zone than Manson-Coffin method. The life prediction results of two methods for TC4 titanium alloy prove better than TC11 titanium alloy.

SIFTER search: a web server for accurate phylogeny-based protein function prediction

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

Sahraeian, Sayed M.; Luo, Kevin R.; Brenner, Steven E.

We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access tomore » precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. Lastly, the SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.« less

SIFTER search: a web server for accurate phylogeny-based protein function prediction

DOE PAGES

Sahraeian, Sayed M.; Luo, Kevin R.; Brenner, Steven E.

2015-05-15

We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access tomore » precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. Lastly, the SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.« less

Attitudes to predictive DNA testing in familial adenomatous polyposis.

PubMed Central

Whitelaw, S; Northover, J M; Hodgson, S V

1996-01-01

Attitudes to predictive DNA testing for familial adenomatous polyposis were documented in 62 affected adults. Patient views on prenatal testing and termination of pregnancy for this disorder were sought, as were opinions on the most suitable age to offer predictive testing for at risk children and the most appropriate age to begin screening. While 15 (24%) of those questioned stated that they would proceed to termination of pregnancy if a prenatal test indicated that the unborn baby was affected, in clinical practice no one has yet requested this option. Six (10%) people who had refrained from having children for fear of passing on the polyposis gene felt that the arrival of prenatal testing would enable them to consider planning a family. The majority of patients (93%) said they would like their children tested by DNA analysis at birth or in infancy, but felt that 10 to 12 years was the most appropriate time to discuss the diagnosis with the child. PMID:8818937

Prospective Prediction of Functional Difficulties among Recently Separated Veterans

DTIC Science & Technology

2014-01-01

while factors following separation from the military have a primary role in predicting functional difficulties during reintegration into civilian...and protective factors for functional difficulties among Veterans. In a sample of recently separated Marines, we used stepwise logistic and multiple...military, posttraumatic stress disorder, prospective, PTSD, reintegration, risk factors , Veterans, work functioning . INTRODUCTION Studies suggest that Iraq

Revolutionizing Toxicity Testing For Predicting Developmental Outcomes (DNT4)

EPA Science Inventory

Characterizing risk from environmental chemical exposure currently requires extensive animal testing; however, alternative approaches are being researched to increase throughput of chemicals screened, decrease reliance on animal testing, and improve accuracy in predicting adverse...

Functional performance testing for power and return to sports.

PubMed

Manske, Robert; Reiman, Michael

2013-05-01

Functional performance testing of athletes can determine physical limitations that may affect sporting activities. Optimal functional performance testing simulates the athlete's activity. A Medline search from 1960 to 2012 was implemented with the keywords functional testing, functional impairment testing, and functional performance testing in the English language. Each author also undertook independent searches of article references. Functional performance tests can bridge the gap between general physical tests and full, unrestricted athletic activity.

Prediction of biodegradability from chemical structure: Modeling or ready biodegradation test data

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

Loonen, H.; Lindgren, F.; Hansen, B.

1999-08-01

Biodegradation data were collected and evaluated for 894 substances with widely varying chemical structures. All data were determined according to the Japanese Ministry of International Trade and Industry (MITI) I test protocol. The MITI I test is a screening test for ready biodegradability and has been described by Organization for Economic Cooperation and Development (OECD) test guideline 301 C and European Union (EU) test guideline C4F. The chemicals were characterized by a set of 127 predefined structural fragments. This data set was used to develop a model for the prediction of the biodegradability of chemicals under standardized OECD and EUmore » ready biodegradation test conditions. Partial least squares (PLS) discriminant analysis was used for the model development. The model was evaluated by means of internal cross-validation and repeated external validation. The importance of various structural fragments and fragment interactions was investigated. The most important fragments include the presence of a long alkyl chain; hydroxy, ester, and acid groups (enhancing biodegradation); and the presence of one or more aromatic rings and halogen substituents (regarding biodegradation). More than 85% of the model predictions were correct for using the complete data set. The not readily biodegradable predictions were slightly better than the readily biodegradable predictions (86 vs 84%). The average percentage of correct predictions from four external validation studies was 83%. Model optimization by including fragment interactions improve the model predicting capabilities to 89%. It can be concluded that the PLS model provides predictions of high reliability for a diverse range of chemical structures. The predictions conform to the concept of readily biodegradable (or not readily biodegradable) as defined by OECD and EU test guidelines.« less

Prediction of Frequency for Simulation of Asphalt Mix Fatigue Tests Using MARS and ANN

PubMed Central

Fakhri, Mansour

2014-01-01

Fatigue life of asphalt mixes in laboratory tests is commonly determined by applying a sinusoidal or haversine waveform with specific frequency. The pavement structure and loading conditions affect the shape and the frequency of tensile response pulses at the bottom of asphalt layer. This paper introduces two methods for predicting the loading frequency in laboratory asphalt fatigue tests for better simulation of field conditions. Five thousand (5000) four-layered pavement sections were analyzed and stress and strain response pulses in both longitudinal and transverse directions was determined. After fitting the haversine function to the response pulses by the concept of equal-energy pulse, the effective length of the response pulses were determined. Two methods including Multivariate Adaptive Regression Splines (MARS) and Artificial Neural Network (ANN) methods were then employed to predict the effective length (i.e., frequency) of tensile stress and strain pulses in longitudinal and transverse directions based on haversine waveform. It is indicated that, under controlled stress and strain modes, both methods (MARS and ANN) are capable of predicting the frequency of loading in HMA fatigue tests with very good accuracy. The accuracy of ANN method is, however, more than MARS method. It is furthermore shown that the results of the present study can be generalized to sinusoidal waveform by a simple equation. PMID:24688400

The prospect of predictive testing for personal risk: attitudes and decision making.

PubMed

Wroe, A L; Salkovskis, P M; Rimes, K A

1998-06-01

As predictive tests for medical problems such as genetic disorders become more widely available, it becomes increasingly important to understand the processes involved in the decision whether or not to seek testing. This study investigates the decision to pursue the possibility of testing. Individuals (one group who had already contemplated the possibility of predictive testing and one group who had not) were asked to consider predictive testing for several diseases. They rated the likelihood of opting for testing and specified the reasons which they believed had affected their decision. The ratio of the numbers of reasons stated for testing and the numbers of reasons stated against testing was a good predictor of the stated likelihood of testing, particularly when the reasons were weighted by utility (importance). Those who had previously contemplated testing specified more emotional reasons. It is proposed that the decision process is internally logical although it may seem illogical to others due to there being idiosyncratic premises (or reasons) upon which the decision is based. It is concluded that the Utility Theory is a useful basis for describing how people make decisions related to predictive testing; modifications of the theory are proposed.

deepNF: Deep network fusion for protein function prediction.

PubMed

Gligorijevic, Vladimir; Barot, Meet; Bonneau, Richard

2018-06-01

The prevalence of high-throughput experimental methods has resulted in an abundance of large-scale molecular and functional interaction networks. The connectivity of these networks provides a rich source of information for inferring functional annotations for genes and proteins. An important challenge has been to develop methods for combining these heterogeneous networks to extract useful protein feature representations for function prediction. Most of the existing approaches for network integration use shallow models that encounter difficulty in capturing complex and highly-nonlinear network structures. Thus, we propose deepNF, a network fusion method based on Multimodal Deep Autoencoders to extract high-level features of proteins from multiple heterogeneous interaction networks. We apply this method to combine STRING networks to construct a common low-dimensional representation containing high-level protein features. We use separate layers for different network types in the early stages of the multimodal autoencoder, later connecting all the layers into a single bottleneck layer from which we extract features to predict protein function. We compare the cross-validation and temporal holdout predictive performance of our method with state-of-the-art methods, including the recently proposed method Mashup. Our results show that our method outperforms previous methods for both human and yeast STRING networks. We also show substantial improvement in the performance of our method in predicting GO terms of varying type and specificity. deepNF is freely available at: https://github.com/VGligorijevic/deepNF. vgligorijevic@flatironinstitute.org, rb133@nyu.edu. Supplementary data are available at Bioinformatics online.

Functional Performance Testing for Power and Return to Sports

PubMed Central

Manske, Robert; Reiman, Michael

2013-01-01

Context: Functional performance testing of athletes can determine physical limitations that may affect sporting activities. Optimal functional performance testing simulates the athlete’s activity. Evidence Acquisition: A Medline search from 1960 to 2012 was implemented with the keywords functional testing, functional impairment testing, and functional performance testing in the English language. Each author also undertook independent searches of article references. Conclusion: Functional performance tests can bridge the gap between general physical tests and full, unrestricted athletic activity. PMID:24427396

Prediction of in-season shoulder injury from preseason testing in division I collegiate football players.

PubMed

Pontillo, Marisa; Spinelli, Bryan A; Sennett, Brian J

2014-11-01

Collegiate football is a high-demand sport in which shoulder injuries are common. Research has described the incidence of these injuries, with little focus on causative factors or injury prevention. Football athletes who score lower on preseason strength and functional testing are more likely to sustain an in-season shoulder injury. Prospective, cohort study. Level 2. Twenty-six collegiate football players underwent preseason testing with a rotational profile for shoulder range of motion, isometric strength of the rotator cuff at 90° elevation and external rotation in the 90/90 position, fatigue testing (prone-Y, scaption, and standing cable press), and the Closed Kinetic Chain Upper Extremity Stability Test (CKCUEST). Data collected postseason included the type of shoulder injury and the side injured. Logistic regression was used to determine if the testing measures predicted injury, and a receiver operating characteristic curve was constructed to examine the relationship of CKCUEST to injury. Six athletes sustained shoulder injuries during the season. Predictor variables could significantly predict whether that player would sustain an injury during the season for both the right and left shoulders (P < 0.05). The variables that were significantly correlated with injury of the right side were forward elevation strength, prone-Y to fatigue, and the CKCUEST (P < 0.05); on the left, only the CKCUEST was significant (P < 0.05). The area under the receiver operating characteristic curve for the CKCUEST was 0.86 (ϵ = 0.87, P = 0.01). Using a score of 21 touches, the CKCUEST had a sensitivity of 0.83, a specificity of 0.79, and an odds ratio of 18.75 in determining whether a player sustained a shoulder injury. For this sample, the combination of preseason strength, fatigue, and functional testing was able to identify football players who would sustain a shoulder injury during the season. Using a battery of strength, fatigue, and functional testing may be helpful in

Nonparametric predictive inference for combining diagnostic tests with parametric copula

NASA Astrophysics Data System (ADS)

Muhammad, Noryanti; Coolen, F. P. A.; Coolen-Maturi, T.

2017-09-01

Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine and health care. The Receiver Operating Characteristic (ROC) curve is a popular statistical tool for describing the performance of diagnostic tests. The area under the ROC curve (AUC) is often used as a measure of the overall performance of the diagnostic test. In this paper, we interest in developing strategies for combining test results in order to increase the diagnostic accuracy. We introduce nonparametric predictive inference (NPI) for combining two diagnostic test results with considering dependence structure using parametric copula. NPI is a frequentist statistical framework for inference on a future observation based on past data observations. NPI uses lower and upper probabilities to quantify uncertainty and is based on only a few modelling assumptions. While copula is a well-known statistical concept for modelling dependence of random variables. A copula is a joint distribution function whose marginals are all uniformly distributed and it can be used to model the dependence separately from the marginal distributions. In this research, we estimate the copula density using a parametric method which is maximum likelihood estimator (MLE). We investigate the performance of this proposed method via data sets from the literature and discuss results to show how our method performs for different family of copulas. Finally, we briefly outline related challenges and opportunities for future research.

The influence of a wall function on turbine blade heat transfer prediction

NASA Technical Reports Server (NTRS)

Whitaker, Kevin W.

1989-01-01

The second phase of a continuing investigation to improve the prediction of turbine blade heat transfer coefficients was completed. The present study specifically investigated how a numeric wall function in the turbulence model of a two-dimensional boundary layer code, STAN5, affected heat transfer prediction capabilities. Several sources of inaccuracy in the wall function were identified and then corrected or improved. Heat transfer coefficient predictions were then obtained using each one of the modifications to determine its effect. Results indicated that the modifications made to the wall function can significantly affect the prediction of heat transfer coefficients on turbine blades. The improvement in accuracy due the modifications is still inconclusive and is still being investigated.

Slash prediction: a test in commercial thinnings in northeasrern California

Treesearch

C. Phillip Weatherspoon; Gary O. Fiddler

1984-01-01

Two slash prediction handbooks commonly used in California do not use data from California. To test predictions of the handbooks in northeastern California, logging residues from commercially thinned young-growth stands were surveyed. Measured residues were compared to handbook predictions. Species represented were ponderosa pine, California white fir, California red...

Protein function prediction using neighbor relativity in protein-protein interaction network.

PubMed

Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

2013-04-01

There is a large gap between the number of discovered proteins and the number of functionally annotated ones. Due to the high cost of determining protein function by wet-lab research, function prediction has become a major task for computational biology and bioinformatics. Some researches utilize the proteins interaction information to predict function for un-annotated proteins. In this paper, we propose a novel approach called "Neighbor Relativity Coefficient" (NRC) based on interaction network topology which estimates the functional similarity between two proteins. NRC is calculated for each pair of proteins based on their graph-based features including distance, common neighbors and the number of paths between them. In order to ascribe function to an un-annotated protein, NRC estimates a weight for each neighbor to transfer its annotation to the unknown protein. Finally, the unknown protein will be annotated by the top score transferred functions. We also investigate the effect of using different coefficients for various types of functions. The proposed method has been evaluated on Saccharomyces cerevisiae and Homo sapiens interaction networks. The performance analysis demonstrates that NRC yields better results in comparison with previous protein function prediction approaches that utilize interaction network. Copyright © 2012 Elsevier Ltd. All rights reserved.

Domains of cognitive function in early old age: which ones are predicted by pre-retirement psychosocial work characteristics?

PubMed

Sabbath, Erika L; Andel, Ross; Zins, Marie; Goldberg, Marcel; Berr, Claudine

2016-10-01

Psychosocial work characteristics may predict cognitive functioning after retirement. However, little research has explored specific cognitive domains associated with psychosocial work environments. Our study tested whether exposure to job demands, job control and their combination during working life predicted post-retirement performance on eight cognitive tests. We used data from French GAZEL cohort members who had undergone post-retirement cognitive testing (n=2149). Psychosocial job characteristics were measured on average for 4 years before retirement using Karasek's Job Content Questionnaire (job demands, job control and demand-control combinations). We tested associations between these exposures and post-retirement performance on tests for executive function, visual-motor speed, psychomotor speed, verbal memory, and verbal fluency using ordinary least squares regression. Low job control during working life was negatively associated with executive function, psychomotor speed, phonemic fluency and semantic fluency after retirement (p's<0.05), even after adjustment for demographics, socioeconomic status, health and social behaviours and vascular risk factors. Both passive (low-demand, low-control) and high-strain (high-demand, low-control) jobs were associated with lower scores on phonemic and semantic fluency when compared to low-strain (low-demand, high-control) jobs. Low job control, in combination with both high and low-job demands, is associated with post-retirement deficits in some, but not all, cognitive domains. In addition to work stress, associations between passive work and subsequent cognitive function may implicate lack of cognitive engagement at work as a risk factor for future cognitive difficulties. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Bayesian modelling of lung function data from multiple-breath washout tests.

PubMed

Mahar, Robert K; Carlin, John B; Ranganathan, Sarath; Ponsonby, Anne-Louise; Vuillermin, Peter; Vukcevic, Damjan

2018-05-30

Paediatric respiratory researchers have widely adopted the multiple-breath washout (MBW) test because it allows assessment of lung function in unsedated infants and is well suited to longitudinal studies of lung development and disease. However, a substantial proportion of MBW tests in infants fail current acceptability criteria. We hypothesised that a model-based approach to analysing the data, in place of traditional simple empirical summaries, would enable more efficient use of these tests. We therefore developed a novel statistical model for infant MBW data and applied it to 1197 tests from 432 individuals from a large birth cohort study. We focus on Bayesian estimation of the lung clearance index, the most commonly used summary of lung function from MBW tests. Our results show that the model provides an excellent fit to the data and shed further light on statistical properties of the standard empirical approach. Furthermore, the modelling approach enables the lung clearance index to be estimated by using tests with different degrees of completeness, something not possible with the standard approach. Our model therefore allows previously unused data to be used rather than discarded, as well as routine use of shorter tests without significant loss of precision. Beyond our specific application, our work illustrates a number of important aspects of Bayesian modelling in practice, such as the importance of hierarchical specifications to account for repeated measurements and the value of model checking via posterior predictive distributions. Copyright © 2018 John Wiley & Sons, Ltd.

Predictive values of thermal and electrical dental pulp tests: a clinical study.

PubMed

Villa-Chávez, Carlos E; Patiño-Marín, Nuria; Loyola-Rodríguez, Juan P; Zavala-Alonso, Norma V; Martínez-Castañón, Gabriel A; Medina-Solís, Carlo E

2013-08-01

For a diagnostic test to be useful, it is necessary to determine the probability that the test will provide the correct diagnosis. Therefore, it is necessary to calculate the predictive value of diagnostics. The aim of the present study was to identify the sensitivity, specificity, positive and negative predictive values, accuracy, and reproducibility of thermal and electrical tests of pulp sensitivity. The thermal tests studied were the 1, 1, 1, 2-tetrafluoroethane (cold) and hot gutta-percha (hot) tests. For the electrical test, the Analytic Technology Pulp Tester (Analytic Technology, Redmond, WA) was used. A total of 110 teeth were tested: 60 teeth with vital pulp and 50 teeth with necrotic pulps (disease prevalence of 45%). The ideal standard was established by direct pulp inspection. The sensitivities of the diagnostic tests were 0.88 for the cold test, 0.86 for the heat test, and 0.76 for the electrical test, and the specificity was 1.0 for all 3 tests. The negative predictive value was 0.90 for the cold test, 0.89 for the heat test, and 0.83 for the electrical test, and the positive predictive value was 1.0 for all 3 tests. The highest accuracy (0.94) and reproducibility (0.88) were observed for the cold test. The cold test was the most accurate method for diagnostic testing. Copyright © 2013 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Validity of Integrity Tests for Predicting Drug and Alcohol Abuse

DTIC Science & Technology

1993-08-31

Wiinkler and Sheridan (1989) found that employees who entered employee assistance programs for treating drug addiction were more likely be absent...August 31, 1993 Final 4. TITLE AND SUBTITLE S. FUNDING NUMBERS Validity of Integrity Tests for Predicting Drug and Alcohol Abuse C No. N00014-92-J...words) This research used psychometric meta-analysis (Hunter & Schmidt, 1990b) to examine the validity of integrity tests for predicting drug and

Predicting the thermodynamic stability of double-perovskite halides from density functional theory

DOE PAGES

Han, Dan; Zhang, Tao; Huang, Menglin; ...

2018-05-24

Recently, a series of double-perovskite halide compounds such as Cs 2AgBiCl 6 and Cs 2AgBiBr 6 have attracted intensive interest as promising alternatives to the solar absorber material CH 3NH 3PbI 3 because they are Pb-free and may exhibit enhanced stability. The thermodynamic stability of a number of double-perovskite halides has been predicted based on density functional theory (DFT) calculations of compound formation energies. In this paper, we found that the stability prediction can be dependent on the approximations used for the exchange-correlation functionals, e.g., the DFT calculations using the widely used Perdew, Burke, Ernzerhof (PBE) functional predict that Csmore » 2AgBiBr 6 is thermodynamically unstable against phase-separation into the competing phases such as AgBr, Cs 2AgBr 3, Cs 3Bi 2Br 9, etc., obviously inconsistent with the good stability observed experimentally. The incorrect prediction by the PBE calculation results from its failure to predict the correct ground-state structures of AgBr, AgCl, and CsCl. By contrast, the DFT calculations based on local density approximation, optB86b-vdW, and optB88-vdW functionals predict the ground-state structures of these binary halides correctly. Furthermore, the optB88-vdW functional is found to give the most accurate description of the lattice constants of the double-perovskite halides and their competing phases. Given these two aspects, we suggest that the optB88-vdW functional should be used for predicting thermodynamic stability in the future high-throughput computational material design or the construction of the Materials Genome database for new double-perovskite halides. As a result, using different exchange-correlation functionals has little influence on the dispersion of the conduction and the valence bands near the electronic bandgap; however, the calculated bandgap can be affected indirectly by the optimized lattice constant, which varies for different functionals.« less

Predicting the thermodynamic stability of double-perovskite halides from density functional theory

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

Han, Dan; Zhang, Tao; Huang, Menglin

Recently, a series of double-perovskite halide compounds such as Cs 2AgBiCl 6 and Cs 2AgBiBr 6 have attracted intensive interest as promising alternatives to the solar absorber material CH 3NH 3PbI 3 because they are Pb-free and may exhibit enhanced stability. The thermodynamic stability of a number of double-perovskite halides has been predicted based on density functional theory (DFT) calculations of compound formation energies. In this paper, we found that the stability prediction can be dependent on the approximations used for the exchange-correlation functionals, e.g., the DFT calculations using the widely used Perdew, Burke, Ernzerhof (PBE) functional predict that Csmore » 2AgBiBr 6 is thermodynamically unstable against phase-separation into the competing phases such as AgBr, Cs 2AgBr 3, Cs 3Bi 2Br 9, etc., obviously inconsistent with the good stability observed experimentally. The incorrect prediction by the PBE calculation results from its failure to predict the correct ground-state structures of AgBr, AgCl, and CsCl. By contrast, the DFT calculations based on local density approximation, optB86b-vdW, and optB88-vdW functionals predict the ground-state structures of these binary halides correctly. Furthermore, the optB88-vdW functional is found to give the most accurate description of the lattice constants of the double-perovskite halides and their competing phases. Given these two aspects, we suggest that the optB88-vdW functional should be used for predicting thermodynamic stability in the future high-throughput computational material design or the construction of the Materials Genome database for new double-perovskite halides. As a result, using different exchange-correlation functionals has little influence on the dispersion of the conduction and the valence bands near the electronic bandgap; however, the calculated bandgap can be affected indirectly by the optimized lattice constant, which varies for different functionals.« less

Behavioral, Brain Imaging and Genomic Measures to Predict Functional Outcomes Post - Bed Rest and Spaceflight

NASA Technical Reports Server (NTRS)

Mulavara, A. P.; DeDios, Y. E.; Gadd, N. E.; Caldwell, E. E.; Batson, C. D.; Goel, R.; Seidler, R. D.; Oddsson, L.; Zanello, S.; Clarke, T.;

Weaknesses in executive functioning predict the initiating of adolescents' alcohol use.

PubMed

Peeters, Margot; Janssen, Tim; Monshouwer, Karin; Boendermaker, Wouter; Pronk, Thomas; Wiers, Reinout; Vollebergh, Wilma

2015-12-01

Recently, it has been suggested that impairments in executive functioning might be risk factors for the onset of alcohol use rather than a result of heavy alcohol use. In the present study, we examined whether two aspects of executive functioning, working memory and response inhibition, predicted the first alcoholic drink and first binge drinking episode in young adolescents using discrete survival analyses. Adolescents were selected from several Dutch secondary schools including both mainstream and special education (externalizing behavioral problems). Participants were 534 adolescents between 12 and 14 years at baseline. Executive functioning and alcohol use were assessed four times over a period of two years. Working memory uniquely predicted the onset of first drink (p=.01) and first binge drinking episode (p=.04) while response inhibition only uniquely predicted the initiating of the first drink (p=.01). These results suggest that the association of executive functioning and alcohol consumption found in former studies cannot simply be interpreted as an effect of alcohol consumption, as weaknesses in executive functioning, found in alcohol naïve adolescents, predict the initiating of (binge) drinking. Though, prolonged and heavy alcohol use might further weaken already existing deficiencies. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Nominal and functional task difficulty in skill acquisition: Effects on performance in two tests of transfer.

PubMed

Sanli, Elizabeth A; Lee, Timothy D

2015-06-01

The influence of nominal and functional task difficulty during the acquisition of a motor skill was examined in two tests of transfer of learning. The task involved a ballistic, target-directed, finger action. Nominal task difficulty was defined as the distance of the target from the home position. Functional task difficulty was created by manipulating the progression of target distances during practice. Based on the challenge point framework (Guadagnoli & Lee, 2004), we predicted that practice with a set of targets farther away from the performer would benefit from less functional task difficulty, while practice with a closer set of targets would benefit from more functional task difficulty. In single-task transfer tests, learners who practiced using the high nominal task difficulty targets benefitted in terms of persistence of performance over time. In dual-task transfer tests, groups with an intermediate combined (nominal and functional) task difficulty performed with greater persistence over time on tests of transfer than those who practiced with the highest or lowest combined difficulty. Together these findings suggest that the influences of nominal and functional task difficulty during acquisition are weighted differentially depending upon the transfer test context. The challenge point framework does not accurately capture this complex relationship in its current form. Copyright © 2015 Elsevier B.V. All rights reserved.

Behavioral, Brain Imaging and Genomic Measures to Predict Functional Outcomes Post-Bed Rest and Space Flight

NASA Technical Reports Server (NTRS)

Mulavara, A. P.; Peters, B.; De Dios, Y. E.; Gadd, N. E.; Caldwell, E. E.; Batson, C. D.; Goel, R.; Oddsson, L.; Kreutzberg, G.; Zanello, S.;

Pretest Predictions for Phase II Ventilation Tests

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

Yiming Sun

The objective of this calculation is to predict the temperatures of the ventilating air, waste package surface, and concrete pipe walls that will be developed during the Phase II ventilation tests involving various test conditions. The results will be used as inputs to validating numerical approach for modeling continuous ventilation, and be used to support the repository subsurface design. The scope of the calculation is to identify the physical mechanisms and parameters related to thermal response in the Phase II ventilation tests, and describe numerical methods that are used to calculate the effects of continuous ventilation. The calculation is limitedmore » to thermal effect only. This engineering work activity is conducted in accordance with the ''Technical Work Plan for: Subsurface Performance Testing for License Application (LA) for Fiscal Year 2001'' (CRWMS M&O 2000d). This technical work plan (TWP) includes an AP-2.21Q, ''Quality Determinations and Planning for Scientific, Engineering, and Regulatory Compliance Activities'', activity evaluation (CRWMS M&O 2000d, Addendum A) that has determined this activity is subject to the YMP quality assurance (QA) program. The calculation is developed in accordance with the AP-3.12Q procedure, ''Calculations''. Additional background information regarding this activity is contained in the ''Development Plan for Ventilation Pretest Predictive Calculation'' (DP) (CRWMS M&O 2000a).« less

Are trait-growth models transferable? Predicting multi-species growth trajectories between ecosystems using plant functional traits

PubMed Central

Vesk, Peter A.

2017-01-01

Plant functional traits are increasingly used to generalize across species, however few examples exist of predictions from trait-based models being evaluated in new species or new places. Can we use functional traits to predict growth of unknown species in different areas? We used three independently collected datasets, each containing data on heights of individuals from non-resprouting species over a chronosquence of time-since-fire sites from three ecosystems in south-eastern Australia. We examined the influence of specific leaf area, woody density, seed size and leaf nitrogen content on three aspects of plant growth; maximum relative growth rate, age at maximum growth and asymptotic height. We tested our capacity to perform out-of-sample prediction of growth trajectories between ecosystems using species functional traits. We found strong trait-growth relationships in one of the datasets; whereby species with low SLA achieved the greatest asymptotic heights, species with high leaf-nitrogen content achieved relatively fast growth rates, and species with low seed mass reached their time of maximum growth early. However these same growth-trait relationships did not hold across the two other datasets, making accurate prediction from one dataset to another unachievable. We believe there is evidence to suggest that growth trajectories themselves may be fundamentally different between ecosystems and that trait-height-growth relationships may change over environmental gradients. PMID:28486535

Using PPI network autocorrelation in hierarchical multi-label classification trees for gene function prediction.

PubMed

Stojanova, Daniela; Ceci, Michelangelo; Malerba, Donato; Dzeroski, Saso

2013-09-26

Ontologies and catalogs of gene functions, such as the Gene Ontology (GO) and MIPS-FUN, assume that functional classes are organized hierarchically, that is, general functions include more specific ones. This has recently motivated the development of several machine learning algorithms for gene function prediction that leverages on this hierarchical organization where instances may belong to multiple classes. In addition, it is possible to exploit relationships among examples, since it is plausible that related genes tend to share functional annotations. Although these relationships have been identified and extensively studied in the area of protein-protein interaction (PPI) networks, they have not received much attention in hierarchical and multi-class gene function prediction. Relations between genes introduce autocorrelation in functional annotations and violate the assumption that instances are independently and identically distributed (i.i.d.), which underlines most machine learning algorithms. Although the explicit consideration of these relations brings additional complexity to the learning process, we expect substantial benefits in predictive accuracy of learned classifiers. This article demonstrates the benefits (in terms of predictive accuracy) of considering autocorrelation in multi-class gene function prediction. We develop a tree-based algorithm for considering network autocorrelation in the setting of Hierarchical Multi-label Classification (HMC). We empirically evaluate the proposed algorithm, called NHMC (Network Hierarchical Multi-label Classification), on 12 yeast datasets using each of the MIPS-FUN and GO annotation schemes and exploiting 2 different PPI networks. The results clearly show that taking autocorrelation into account improves the predictive performance of the learned models for predicting gene function. Our newly developed method for HMC takes into account network information in the learning phase: When used for gene function

Predicting bending strength of fire-retardant-treated plywood from screw-withdrawal tests

Treesearch

J. E. Winandy; P. K. Lebow; W. Nelson

This report describes the development of a test method and predictive model to estimate the residual bending strength of fire-retardant-treated plywood roof sheathing from measurement of screw-withdrawal force. The preferred test methodology is described in detail. Models were developed to predict loss in mean and lower prediction bounds for plywood bending strength as...

Transfer of function and prior derived-relations testing.

PubMed

Doughty, Adam H; Best, Lauren

2017-10-01

This experiment assessed transfer of function through equivalence relations with and without prior derived-stimulus-relations (DSR) testing. In a DSR-Testing Group, eight college students learned A-B and A-C discriminations in baseline. They then derived the B-C and C-B equivalence relations before being exposed to a transfer-of-function manipulation and test. Eight participants in a No-DSR Testing Group were exposed to the transfer-of-function manipulation and test immediately after learning the baseline discriminations (i.e., B-C and C-B testing were omitted). In the transfer-of-function manipulation, participants learned to respond differently in the presence of B1 and B2 to avoid money loss. In the transfer-of-function test, responding in the presence of C1 and C2 was measured in the absence of differential consequences. Transfer of function occurred reliably only in the DSR-Testing Group (i.e., participants responding to C1 and C2 in the manner they learned to respond to B1 and B2, respectively). These findings support the notion that prior DSR testing can be critical to observing transfer of function. Copyright © 2017 Elsevier B.V. All rights reserved.

Implications of the International Classification of Functioning, Disability and Health (ICF) for Test Development and Use

ERIC Educational Resources Information Center

Carlson, Janet F.; Benson, Nicholas; Oakland, Thomas

2010-01-01

Implications of the International Classification of Functioning, Disability and Health (ICF) on the development and use of tests in school settings are enumerated. We predict increased demand for behavioural assessments that consider a person's activities, participation and person-environment interactions, including measures that: (a) address…

Variation in trait trade-offs allows differentiation among predefined plant functional types: implications for predictive ecology.

PubMed

Verheijen, Lieneke M; Aerts, Rien; Bönisch, Gerhard; Kattge, Jens; Van Bodegom, Peter M

2016-01-01

Plant functional types (PFTs) aggregate the variety of plant species into a small number of functionally different classes. We examined to what extent plant traits, which reflect species' functional adaptations, can capture functional differences between predefined PFTs and which traits optimally describe these differences. We applied Gaussian kernel density estimation to determine probability density functions for individual PFTs in an n-dimensional trait space and compared predicted PFTs with observed PFTs. All possible combinations of 1-6 traits from a database with 18 different traits (total of 18 287 species) were tested. A variety of trait sets had approximately similar performance, and 4-5 traits were sufficient to classify up to 85% of the species into PFTs correctly, whereas this was 80% for a bioclimatically defined tree PFT classification. Well-performing trait sets included combinations of correlated traits that are considered functionally redundant within a single plant strategy. This analysis quantitatively demonstrates how structural differences between PFTs are reflected in functional differences described by particular traits. Differentiation between PFTs is possible despite large overlap in plant strategies and traits, showing that PFTs are differently positioned in multidimensional trait space. This study therefore provides the foundation for important applications for predictive ecology. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

The predictive value of cerebrospinal fluid tap-test in normal pressure hydrocephalus.

PubMed

Damasceno, B P; Carelli, E F; Honorato, D C; Facure, J J

1997-06-01

Eighteen patients (mean age of 66.5 years) with normal pressure hydrocephalus (NPH) underwent a ventriculo-peritoneal shunt surgery. Prior to operation a cerebrospinal fluid tap-test (CSF-TT) was performed with measurements of gait pattern and psychometric functions (memory, visuo-motor speed and visuo-constructive skills) before and after the removal of 50 ml CSF by lumbar puncture (LP). Fifteen patients improved and 3 were unchanged after surgery. Short duration of disease, gait disturbance preceding mental deterioration, wide temporal horns and small sulci on CT-scan were associated with good outcome after shunting. There was a good correlation between the results of CSF-TT and shunt surgery (chi 2 = 4.11, phi = 0.48, p < 0.05), with gait test showing highest correlation (r = 0.99, p = 0.01). In conclusion, this version of CSF-TT proved to be an effective test to predict improvement after shunting in patients with NPH.

Predicting taxonomic and functional structure of microbial communities in acid mine drainage

PubMed Central

Kuang, Jialiang; Huang, Linan; He, Zhili; Chen, Linxing; Hua, Zhengshuang; Jia, Pu; Li, Shengjin; Liu, Jun; Li, Jintian; Zhou, Jizhong; Shu, Wensheng

2016-01-01

Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic β-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray–Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural

Predicting taxonomic and functional structure of microbial communities in acid mine drainage.

PubMed

Kuang, Jialiang; Huang, Linan; He, Zhili; Chen, Linxing; Hua, Zhengshuang; Jia, Pu; Li, Shengjin; Liu, Jun; Li, Jintian; Zhou, Jizhong; Shu, Wensheng

2016-06-01

Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic β-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray-Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural

Link prediction boosted psychiatry disorder classification for functional connectivity network

NASA Astrophysics Data System (ADS)

Li, Weiwei; Mei, Xue; Wang, Hao; Zhou, Yu; Huang, Jiashuang

2017-02-01

Functional connectivity network (FCN) is an effective tool in psychiatry disorders classification, and represents cross-correlation of the regional blood oxygenation level dependent signal. However, FCN is often incomplete for suffering from missing and spurious edges. To accurate classify psychiatry disorders and health control with the incomplete FCN, we first `repair' the FCN with link prediction, and then exact the clustering coefficients as features to build a weak classifier for every FCN. Finally, we apply a boosting algorithm to combine these weak classifiers for improving classification accuracy. Our method tested by three datasets of psychiatry disorder, including Alzheimer's Disease, Schizophrenia and Attention Deficit Hyperactivity Disorder. The experimental results show our method not only significantly improves the classification accuracy, but also efficiently reconstructs the incomplete FCN.

Test prediction for the German PKL Test K5A using RELAP4/MOD6

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

Chen, Y.S.; Haigh, W.S.; Sullivan, L.H.

RELAP4/MOD6 is the most recent modification in the series of RELAP4 computer programs developed to describe the thermal-hydraulic conditions attendant to postulated transients in light water reactor systems. The major new features in RELAP4/MOD6 include best-estimate pressurized water reactor (PWR) reflood transient analytical models for core heat transfer, local entrainment, and core vapor superheat, and a new set of heat transfer correlations for PWR blowdown and reflood. These new features were used for a test prediction of the Kraftwerk Union three-loop PRIMAR KREISLAUF (PKL) Reflood Test K5A. The results of the prediction were in good agreement with the experimental thermalmore » and hydraulic system data. Comparisons include heater rod surface temperature, system pressure, mass flow rates, and core mixture level. It is concluded that RELAP4/MOD6 is capable of accurately predicting transient reflood phenomena in the 200% cold-leg break test configuration of the PKL reflood facility.« less

Handgrip Strength Predicts Functional Decline at Discharge in Hospitalized Male Elderly: A Hospital Cohort Study

PubMed Central

García-Peña, Carmen; García-Fabela, Luis C.; Gutiérrez-Robledo, Luis M.; García-González, Jose J.; Arango-Lopera, Victoria E.; Pérez-Zepeda, Mario U.

2013-01-01

Functional decline after hospitalization is a common adverse outcome in elderly. An easy to use, reproducible and accurate tool to identify those at risk would aid focusing interventions in those at higher risk. Handgrip strength has been shown to predict adverse outcomes in other settings. The aim of this study was to determine if handgrip strength measured upon admission to an acute care facility would predict functional decline (either incident or worsening of preexisting) at discharge among older Mexican, stratified by gender. In addition, cutoff points as a function of specificity would be determined. A cohort study was conducted in two hospitals in Mexico City. The primary endpoint was functional decline on discharge, defined as a 30-point reduction in the Barthel Index score from that of the baseline score. Handgrip strength along with other variables was measured at initial assessment, including: instrumental activities of daily living, cognition, depressive symptoms, delirium, hospitalization length and quality of life. All analyses were stratified by gender. Logistic regression to test independent association between handgrip strength and functional decline was performed, along with estimation of handgrip strength test values (specificity, sensitivity, area under the curve, etc.). A total of 223 patients admitted to an acute care facility between 2007 and 2009 were recruited. A total of 55 patients (24.7%) had functional decline, 23.46% in male and 25.6% in women. Multivariate analysis showed that only males with low handgrip strength had an increased risk of functional decline at discharge (OR 0.88, 95% CI 0.79–0.98, p = 0.01), with a specificity of 91.3% and a cutoff point of 20.65 kg for handgrip strength. Females had not a significant association between handgrip strength and functional decline. Measurement of handgrip strength on admission to acute care facilities may identify male elderly patients at risk of having functional decline, and

Adolescents’ Functional Numeracy Is Predicted by Their School Entry Number System Knowledge

PubMed Central

Geary, David C.; Hoard, Mary K.; Nugent, Lara; Bailey, Drew H.

2013-01-01

One in five adults in the United States is functionally innumerate; they do not possess the mathematical competencies needed for many modern jobs. We administered functional numeracy measures used in studies of young adults’ employability and wages to 180 thirteen-year-olds. The adolescents began the study in kindergarten and participated in multiple assessments of intelligence, working memory, mathematical cognition, achievement, and in-class attentive behavior. Their number system knowledge at the beginning of first grade was defined by measures that assessed knowledge of the systematic relations among Arabic numerals and skill at using this knowledge to solve arithmetic problems. Early number system knowledge predicted functional numeracy more than six years later (ß = 0.195, p = .0014) controlling for intelligence, working memory, in-class attentive behavior, mathematical achievement, demographic and other factors, but skill at using counting procedures to solve arithmetic problems did not. In all, we identified specific beginning of schooling numerical knowledge that contributes to individual differences in adolescents’ functional numeracy and demonstrated that performance on mathematical achievement tests underestimates the importance of this early knowledge. PMID:23382934

Routine blood tests to predict liver fibrosis in chronic hepatitis C.

PubMed

Hsieh, Yung-Yu; Tung, Shui-Yi; Lee, Kamfai; Wu, Cheng-Shyong; Wei, Kuo-Liang; Shen, Chien-Heng; Chang, Te-Sheng; Lin, Yi-Hsiung

2012-02-28

To verify the usefulness of FibroQ for predicting fibrosis in patients with chronic hepatitis C, compared with other noninvasive tests. This retrospective cohort study included 237 consecutive patients with chronic hepatitis C who had undergone percutaneous liver biopsy before treatment. FibroQ, aspartate aminotransferase (AST)/alanine aminotransferase ratio (AAR), AST to platelet ratio index, cirrhosis discriminant score, age-platelet index (API), Pohl score, FIB-4 index, and Lok's model were calculated and compared. FibroQ, FIB-4, AAR, API and Lok's model results increased significantly as fibrosis advanced (analysis of variance test: P < 0.001). FibroQ trended to be superior in predicting significant fibrosis score in chronic hepatitis C compared with other noninvasive tests. FibroQ is a simple and useful test for predicting significant fibrosis in patients with chronic hepatitis C.

Testing time-dependent density functional theory with depopulated molecular orbitals for predicting electronic excitation energies of valence, Rydberg, and charge-transfer states and potential energies near a conical intersection

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

Li, Shaohong L.; Truhlar, Donald G., E-mail: truhlar@umn.edu

2014-09-14

Kohn-Sham (KS) time-dependent density functional theory (TDDFT) with most exchange-correlation functionals is well known to systematically underestimate the excitation energies of Rydberg and charge-transfer excited states of atomic and molecular systems. To improve the description of Rydberg states within the KS TDDFT framework, Gaiduk et al. [Phys. Rev. Lett. 108, 253005 (2012)] proposed a scheme that may be called HOMO depopulation. In this study, we tested this scheme on an extensive dataset of valence and Rydberg excitation energies of various atoms, ions, and molecules. It is also tested on a charge-transfer excitation of NH{sub 3}-F{sub 2} and on the potentialmore » energy curves of NH{sub 3} near a conical intersection. We found that the method can indeed significantly improve the accuracy of predicted Rydberg excitation energies while preserving reasonable accuracy for valence excitation energies. However, it does not appear to improve the description of charge-transfer excitations that are severely underestimated by standard KS TDDFT with conventional exchange-correlation functionals, nor does it perform appreciably better than standard TDDFT for the calculation of potential energy surfaces.« less

Method and apparatus for transfer function simulator for testing complex systems

NASA Technical Reports Server (NTRS)

Kavaya, M. J. (Inventor)

1985-01-01

A method and apparatus for testing the operation of a complex stabilization circuit in a closed loop system is presented. The method is comprised of a programmed analog or digital computing system for implementing the transfer function of a load thereby providing a predictable load. The digital computing system employs a table stored in a microprocessor in which precomputed values of the load transfer function are stored for values of input signal from the stabilization circuit over the range of interest. This technique may be used not only for isolating faults in the stabilization circuit, but also for analyzing a fault in a faulty load by so varying parameters of the computing system as to simulate operation of the actual load with the fault.

Helicopter external noise prediction and correlation with flight test

NASA Technical Reports Server (NTRS)

Gupta, B. P.

1978-01-01

Mathematical analysis procedures for predicting the main and tail rotor rotational and broadband noise are presented. The aerodynamic and acoustical data from Operational Loads Survey (OLS) flight program are used for validating the analysis and noise prediction methodology. For the long method of rotational noise prediction, the spanwise, chordwise, and azimuthwise airloading is used. In the short method, the airloads are assumed to be concentrated at a single spanwise station and for higher harmonics an airloading harmonic exponent of 2.0 is assumed. For the same flight condition, the predictions from long and short methods of rotational noise prediction are compared with the flight test results. The short method correlates as well or better than the long method.

Predictive Accuracy of Exercise Stress Testing the Healthy Adult.

ERIC Educational Resources Information Center

Lamont, Linda S.

1981-01-01

Exercise stress testing provides information on the aerobic capacity, heart rate, and blood pressure responses to graded exercises of a healthy adult. The reliability of exercise tests as a diagnostic procedure is discussed in relation to sensitivity and specificity and predictive accuracy. (JN)

Ensemble gene function prediction database reveals genes important for complex I formation in Arabidopsis thaliana.

PubMed

Hansen, Bjoern Oest; Meyer, Etienne H; Ferrari, Camilla; Vaid, Neha; Movahedi, Sara; Vandepoele, Klaas; Nikoloski, Zoran; Mutwil, Marek

2018-03-01

Recent advances in gene function prediction rely on ensemble approaches that integrate results from multiple inference methods to produce superior predictions. Yet, these developments remain largely unexplored in plants. We have explored and compared two methods to integrate 10 gene co-function networks for Arabidopsis thaliana and demonstrate how the integration of these networks produces more accurate gene function predictions for a larger fraction of genes with unknown function. These predictions were used to identify genes involved in mitochondrial complex I formation, and for five of them, we confirmed the predictions experimentally. The ensemble predictions are provided as a user-friendly online database, EnsembleNet. The methods presented here demonstrate that ensemble gene function prediction is a powerful method to boost prediction performance, whereas the EnsembleNet database provides a cutting-edge community tool to guide experimentalists. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

The functional head impulse test: preliminary data.

PubMed

Corallo, Giulia; Versino, Maurizio; Mandalà, Marco; Colnaghi, Silvia; Ramat, Stefano

2018-06-04

The functional head impulse test is a new test of vestibular function based on the ability to recognize the orientation of a Landolt C optotype that briefly appears on a computer screen during passive head impulses imposed by the examiner over a range of head accelerations. Here, we compare its results with those of the video head impulse test on a population of vestibular neuritis patients recorded acutely and after 3 months from symptoms onset. The preliminary results presented here show that while both tests are able to identify the affected labyrinth and to show a recovery of vestibular functionality at 3 months, the two tests are not redundant, but complementary.

Evaluation of MELD score and Maddrey discriminant function for mortality prediction in patients with alcoholic hepatitis.

PubMed

Monsanto, Pedro; Almeida, Nuno; Lrias, Clotilde; Pina, Jos Eduardo; Sofia, Carlos

2013-01-01

Maddrey discriminant function (DF) is the traditional model for evaluating the severity and prognosis in alcoholic hepatitis (AH). However, MELD has also been used for this purpose. We aimed to determine the predictive parameters and compare the ability of Maddrey DF and MELD to predict short-term mortality in patients with AH. Retrospective study of 45 patients admitted in our department with AH between 2000 and 2010. Demographic, clinical and laboratory parameters were collected. MELD and Maddrey DF were calculated on admission. Short-term mortality was assessed at 30 and 90 days. Student t-test, χ2 test, univariate analysis, logistic regression and receiver operating characteristic curves were performed. Thirty-day and 90-day mortality was 27% and 42%, respectively. In multivariate analysis, Maddrey DF was the only independent predictor of mortality for these two periods. Receiver operating characteristic curves for Maddrey DF revealed an excellent discriminatory ability to predict 30-day and 90-day mortality for a Maddrey DF greater than 65 and 60, respectively. Discriminatory ability to predict 30-day and 90-day mortality for MELD was low. AH remains associated with a high short-term mortality. Maddrey DF is a more valuable model than MELD to predict short-term mortality in patients with AH.

Thalamic functional connectivity predicts seizure laterality in individual TLE patients: application of a biomarker development strategy.

PubMed

Barron, Daniel S; Fox, Peter T; Pardoe, Heath; Lancaster, Jack; Price, Larry R; Blackmon, Karen; Berry, Kristen; Cavazos, Jose E; Kuzniecky, Ruben; Devinsky, Orrin; Thesen, Thomas

2015-01-01

Noninvasive markers of brain function could yield biomarkers in many neurological disorders. Disease models constrained by coordinate-based meta-analysis are likely to increase this yield. Here, we evaluate a thalamic model of temporal lobe epilepsy that we proposed in a coordinate-based meta-analysis and extended in a diffusion tractography study of an independent patient population. Specifically, we evaluated whether thalamic functional connectivity (resting-state fMRI-BOLD) with temporal lobe areas can predict seizure onset laterality, as established with intracranial EEG. Twenty-four lesional and non-lesional temporal lobe epilepsy patients were studied. No significant differences in functional connection strength in patient and control groups were observed with Mann-Whitney Tests (corrected for multiple comparisons). Notwithstanding the lack of group differences, individual patient difference scores (from control mean connection strength) successfully predicted seizure onset zone as shown in ROC curves: discriminant analysis (two-dimensional) predicted seizure onset zone with 85% sensitivity and 91% specificity; logistic regression (four-dimensional) achieved 86% sensitivity and 100% specificity. The strongest markers in both analyses were left thalamo-hippocampal and right thalamo-entorhinal cortex functional connection strength. Thus, this study shows that thalamic functional connections are sensitive and specific markers of seizure onset laterality in individual temporal lobe epilepsy patients. This study also advances an overall strategy for the programmatic development of neuroimaging biomarkers in clinical and genetic populations: a disease model informed by coordinate-based meta-analysis was used to anatomically constrain individual patient analyses.

Statistical prediction of space motion sickness

NASA Technical Reports Server (NTRS)

Reschke, Millard F.

1990-01-01

Studies designed to empirically examine the etiology of motion sickness to develop a foundation for enhancing its prediction are discussed. Topics addressed include early attempts to predict space motion sickness, multiple test data base that uses provocative and vestibular function tests, and data base subjects; reliability of provocative tests of motion sickness susceptibility; prediction of space motion sickness using linear discriminate analysis; and prediction of space motion sickness susceptibility using the logistic model.

Can we predict functional decline in hospitalized older people admitted through the emergency department? Reanalysis of a predictive tool ten years after its conception.

PubMed

De Brauwer, Isabelle; Cornette, Pascale; Boland, Benoît; Verschuren, Franck; D'Hoore, William

2017-05-12

In the Emergency Department (ED), early and rapid identification of older people at risk of adverse outcomes, who could best benefit from complex geriatric intervention, would avoid wasting time, especially in terms of prevention of adverse outcomes, and ensure optimal orientation of vulnerable patients. We wanted to test the predictive ability of a screening tool assessing risk of functional decline (FD), named SHERPA, 10 years after its conception, and to assess the added value of other clinical or biological factors associated with FD. A prospective cohort study of older patients (n = 305, ≥ 75 years) admitted through the emergency department, for at least 48 h in non-geriatric wards (mean age 82.5 ± 4.9, 55% women). SHERPA variables (i.e. age, pre-admission instrumental Activity of Daily Living (ADL) status, falls within a year, self-rated health and 21-point MMSE) were collected within 48 h of admission, along with socio-demographic, medical and biological data. Functional status was followed at 3 months by phone. FD was defined as a decrease at 3 months of at least one point in the pre-admission basic ADL score. Predictive ability of SHERPA was assessed using c-statistic, predictive values and likelihood ratios. Measures of discrimination improvement were Net Reclassification Improvement and Integrated Discrimination Improvement. One hundred and five patients (34%) developed 3-month FD. Predictive ability of SHERPA decreased dramatically over 10 years (c = 0.73 vs. 0.64). Only two of its constitutive variables, i.e. falls and instrumental ADL, were significant in logistic regression analysis for functional decline, while 21-point MMSE was kept in the model for clinical relevance. Demographic, comorbidity or laboratory data available upon admission did not improve the SHERPA predictive yield. Prediction of FD with SHERPA is difficult, but predictive factors, i.e. falls, pre-existing functional limitation and cognitive impairment, stay

An online study combining the constructs from the theory of planned behaviour and protection motivation theory in predicting intention to test for chlamydia in two testing contexts.

PubMed

Powell, Rachael; Pattison, Helen M; Francis, Jill J

2016-01-01

Chlamydia is a common sexually transmitted infection that has potentially serious consequences unless detected and treated early. The health service in the UK offers clinic-based testing for chlamydia but uptake is low. Identifying the predictors of testing behaviours may inform interventions to increase uptake. Self-tests for chlamydia may facilitate testing and treatment in people who avoid clinic-based testing. Self-testing and being tested by a health care professional (HCP) involve two contrasting contexts that may influence testing behaviour. However, little is known about how predictors of behaviour differ as a function of context. In this study, theoretical models of behaviour were used to assess factors that may predict intention to test in two different contexts: self-testing and being tested by a HCP. Individuals searching for or reading about chlamydia testing online were recruited using Google Adwords. Participants completed an online questionnaire that addressed previous testing behaviour and measured constructs of the Theory of Planned Behaviour and Protection Motivation Theory, which propose a total of eight possible predictors of intention. The questionnaire was completed by 310 participants. Sufficient data for multiple regression were provided by 102 and 118 respondents for self-testing and testing by a HCP respectively. Intention to self-test was predicted by vulnerability and self-efficacy, with a trend-level effect for response efficacy. Intention to be tested by a HCP was predicted by vulnerability, attitude and subjective norm. Thus, intentions to carry out two testing behaviours with very similar goals can have different predictors depending on test context. We conclude that interventions to increase self-testing should be based on evidence specifically related to test context.

Can the calf-raise senior test predict functional fitness in elderly people? A validation study using electromyography, kinematics and strength tests.

PubMed

André, Helô-Isa; Carnide, Filomena; Moço, Andreia; Valamatos, Maria-João; Ramalho, Fátima; Santos-Rocha, Rita; Veloso, António

2018-06-05

The assessment of the plantar-flexors muscle strength in older adults (OA) is of the utmost importance since they are strongly associated with the performance of fundamental tasks of daily life. The objective was to strengthen the validity of the Calf-Raise-Senior (CRS) test by assessing the biomechanical movement pattern of calf muscles in OA with different levels of functional fitness (FF) and physical activity (PA). Twenty-six OA were assessed with CRS, a FF battery, accelerometry, strength tests, kinematics and electromyography (EMG). OA with the best and worst CRS scores were compared. The association between the scores and EMG pattern of ankle muscles was determined. OA with the best CRS scores presented higher levels of FF, PA, strength, power, speed and range of movement, and a more efficient movement pattern during the test. Subjects who scored more at the CRS test demonstrated the possibility to use a stretch-shortening cycle type of action in the PF muscles to increase power during the movements. OA with different levels of FF can be stratified by the muscular activation pattern of the calf muscles and the scores in CRS test. This study reinforced the validity of CRS for evaluating ankle strength and power in OA. Copyright © 2018 Elsevier Ltd. All rights reserved.

Clinical value of CT-based preoperative software assisted lung lobe volumetry for predicting postoperative pulmonary function after lung surgery

NASA Astrophysics Data System (ADS)

Wormanns, Dag; Beyer, Florian; Hoffknecht, Petra; Dicken, Volker; Kuhnigk, Jan-Martin; Lange, Tobias; Thomas, Michael; Heindel, Walter

2005-04-01

This study was aimed to evaluate a morphology-based approach for prediction of postoperative forced expiratory volume in one second (FEV1) after lung resection from preoperative CT scans. Fifteen Patients with surgically treated (lobectomy or pneumonectomy) bronchogenic carcinoma were enrolled in the study. A preoperative chest CT and pulmonary function tests before and after surgery were performed. CT scans were analyzed by prototype software: automated segmentation and volumetry of lung lobes was performed with minimal user interaction. Determined volumes of different lung lobes were used to predict postoperative FEV1 as percentage of the preoperative values. Predicted FEV1 values were compared to the observed postoperative values as standard of reference. Patients underwent lobectomy in twelve cases (6 upper lobes; 1 middle lobe; 5 lower lobes; 6 right side; 6 left side) and pneumonectomy in three cases. Automated calculation of predicted postoperative lung function was successful in all cases. Predicted FEV1 ranged from 54% to 95% (mean 75% +/- 11%) of the preoperative values. Two cases with obviously erroneous LFT were excluded from analysis. Mean error of predicted FEV1 was 20 +/- 160 ml, indicating absence of systematic error; mean absolute error was 7.4 +/- 3.3% respective 137 +/- 77 ml/s. The 200 ml reproducibility criterion for FEV1 was met in 11 of 13 cases (85%). In conclusion, software-assisted prediction of postoperative lung function yielded a clinically acceptable agreement with the observed postoperative values. This method might add useful information for evaluation of functional operability of patients with lung cancer.

Development and validation of a subject-specific finite element model of the functional spinal unit to predict vertebral strength.

PubMed

Lee, Chu-Hee; Landham, Priyan R; Eastell, Richard; Adams, Michael A; Dolan, Patricia; Yang, Lang

2017-09-01

Finite element models of an isolated vertebral body cannot accurately predict compressive strength of the spinal column because, in life, compressive load is variably distributed across the vertebral body and neural arch. The purpose of this study was to develop and validate a patient-specific finite element model of a functional spinal unit, and then use the model to predict vertebral strength from medical images. A total of 16 cadaveric functional spinal units were scanned and then tested mechanically in bending and compression to generate a vertebral wedge fracture. Before testing, an image processing and finite element analysis framework (SpineVox-Pro), developed previously in MATLAB using ANSYS APDL, was used to generate a subject-specific finite element model with eight-node hexahedral elements. Transversely isotropic linear-elastic material properties were assigned to vertebrae, and simple homogeneous linear-elastic properties were assigned to the intervertebral disc. Forward bending loading conditions were applied to simulate manual handling. Results showed that vertebral strengths measured by experiment were positively correlated with strengths predicted by the functional spinal unit finite element model with von Mises or Drucker-Prager failure criteria ( R 2  = 0.80-0.87), with areal bone mineral density measured by dual-energy X-ray absorptiometry ( R 2  = 0.54) and with volumetric bone mineral density from quantitative computed tomography ( R 2  = 0.79). Large-displacement non-linear analyses on all specimens did not improve predictions. We conclude that subject-specific finite element models of a functional spinal unit have potential to estimate the vertebral strength better than bone mineral density alone.

Is low cognitive functioning a predictor or consequence of major depressive disorder? A test in two longitudinal birth cohorts.

PubMed

Schaefer, Jonathan D; Scult, Matthew A; Caspi, Avshalom; Arseneault, Louise; Belsky, Daniel W; Hariri, Ahmad R; Harrington, Honalee; Houts, Renate; Ramrakha, Sandhya; Poulton, Richie; Moffitt, Terrie E

2017-11-16

Cognitive impairment has been identified as an important aspect of major depressive disorder (MDD). We tested two theories regarding the association between MDD and cognitive functioning using data from longitudinal cohort studies. One theory, the cognitive reserve hypothesis, suggests that higher cognitive ability in childhood decreases risk of later MDD. The second, the scarring hypothesis, instead suggests that MDD leads to persistent cognitive deficits following disorder onset. We tested both theories in the Dunedin Study, a population-representative cohort followed from birth to midlife and assessed repeatedly for both cognitive functioning and psychopathology. We also used data from the Environmental Risk Longitudinal Twin Study to test whether childhood cognitive functioning predicts future MDD risk independent of family-wide and genetic risk using a discordant twin design. Contrary to both hypotheses, we found that childhood cognitive functioning did not predict future risk of MDD, nor did study members with a past history of MDD show evidence of greater cognitive decline unless MDD was accompanied by other comorbid psychiatric conditions. Our results thus suggest that low cognitive functioning is related to comorbidity, but is neither an antecedent nor an enduring consequence of MDD. Future research may benefit from considering cognitive deficits that occur during depressive episodes from a transdiagnostic perspective.

Prediction of obeche wood-induced asthma by specific skin prick testing.

PubMed

Hannu, T; Lindström, I; Palmroos, P; Kuuliala, O; Sauni, R

2013-09-01

It has previously been shown that a positive skin prick test (SPT) result is a good predictor of a positive specific inhalation challenge (SIC) in patients with occupational asthma (OA) related to wheat or rye flours. This association has not been previously studied in OA attributable to obeche wood. To describe a clinical series of patients with OA induced by obeche wood. To investigate if the SPT result can be used as a predictor for the outcome of SIC tests. OA was diagnosed according to patient history, lung function examinations and SIC tests, as well as the determination of obeche SPTs. We analysed sensitivity, specificity and positive (PPV) and negative predictive values (NPV) at different wheal sizes of the SPTs and drew receiver-operating characteristic plots using the SIC test result as the gold standard. Obeche wood SIC tests were performed on 34 symptomatic workers. Of these, 27 workers had a positive test result and were diagnosed as having OA. The minimal cut-off value with a PPV of 100% was an SPT wheal of 3.5 mm from obeche wood. This means that all workers with a wheal size of ≥ 3.5 mm from obeche wood had a positive SIC. Positive SPT results in symptomatic workers were good predictors of a positive SIC. SIC with obeche wood may be unnecessary in strongly sensitized workers.

Astronaut Owen Garriott - Test Subject - Human Vestibular Function Experiment

NASA Image and Video Library

1973-08-09

S73-34171 (9 Aug. 1973) --- Scientist-astronaut Owen K. Garriott, Skylab 3 science pilot, serves as test subject for the Skylab ?Human Vestibular Function? M131 Experiment, as seen in this photographic reproduction taken from a television transmission made by a color TV camera aboard the Skylab space station in Earth orbit. The objectives of the Skylab M131 experiment are to obtain data pertinent to establishing the validity of measurements of specific behavioral/physiological responses influenced by vestibular activity under one-g and zero-g conditions; to determine man?s adaptability to unusual vestibular conditions and predict habitability of future spacecraft conditions involving reduced gravity and Coriollis forces; and to measure the accuracy and variability in man?s judgment of spatial coordinates based on atypical gravity receptor cues and inadequate visual cures. Dr. Garriott is seated in the experiment?s litter chair which can rotate the test subject at predetermined rotational velocity or programmed acceleration/decelerational profile. Photo credit: NASA

Neuropsychological Testing Predicts Cerebrospinal Fluid Aβ in Mild Cognitive Impairment (MCI)

PubMed Central

Kandel, Benjamin M.; Avants, Brian B.; Gee, James C.; Arnold, Steven E.; Wolk, David A.

2015-01-01

Background Psychometric tests predict conversion of Mild Cognitive Impairment (MCI) to probable Alzheimer's Disease (AD). Because the definition of clinical AD relies on those same psychometric tests, the ability of these tests to identify underlying AD pathology remains unclear. Objective To determine the degree to which psychometric testing predicts molecular evidence of AD amyloid pathology, as indicated by CSF Aβ1–42, in patients with MCI, as compared to neuroimaging biomarkers. Methods We identified 408 MCI subjects with CSF Aβ levels, psychometric test data, FDG-PET scans, and acceptable volumetric MR scans from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We used psychometric tests and imaging biomarkers in univariate and multivariate models to predict Aβ status. Results The 30-minute delayed recall score of the Rey Auditory Verbal Learning Test (AVLT) was the best predictor of Aβ status among the psychometric tests, achieving an AUC of 0.67±0.02 and odds ratio of 2.5±0.4. FDG-PET was the best imaging-based biomarker (AUC 0.67±0.03, OR 3.2±1.2), followed by hippocampal volume (AUC 0.64±0.02,,OR 2.4±0.3). A multivariate analysis based on the psychometric tests improved on the univariate predictors, achieving an AUC of 0.68±0.03 (OR 3.38±1.2). Adding imaging biomarkers to the multivariate analysis did not improve the AUC. Conclusion Psychometric tests perform as well as imaging biomarkers to predict presence of molecular markers of AD pathology in MCI patients and should be considered in the determination of the likelihood that MCI is due to AD. PMID:25881908

High Precision Prediction of Functional Sites in Protein Structures

PubMed Central

Buturovic, Ljubomir; Wong, Mike; Tang, Grace W.; Altman, Russ B.; Petkovic, Dragutin

2014-01-01

We address the problem of assigning biological function to solved protein structures. Computational tools play a critical role in identifying potential active sites and informing screening decisions for further lab analysis. A critical parameter in the practical application of computational methods is the precision, or positive predictive value. Precision measures the level of confidence the user should have in a particular computed functional assignment. Low precision annotations lead to futile laboratory investigations and waste scarce research resources. In this paper we describe an advanced version of the protein function annotation system FEATURE, which achieved 99% precision and average recall of 95% across 20 representative functional sites. The system uses a Support Vector Machine classifier operating on the microenvironment of physicochemical features around an amino acid. We also compared performance of our method with state-of-the-art sequence-level annotator Pfam in terms of precision, recall and localization. To our knowledge, no other functional site annotator has been rigorously evaluated against these key criteria. The software and predictive models are incorporated into the WebFEATURE service at http://feature.stanford.edu/wf4.0-beta. PMID:24632601

Functionality of empirical model-based predictive analytics for the early detection of hemodynamic instabilty.

PubMed

Summers, Richard L; Pipke, Matt; Wegerich, Stephan; Conkright, Gary; Isom, Kristen C

2014-01-01

Background. Monitoring cardiovascular hemodynamics in the modern clinical setting is a major challenge. Increasing amounts of physiologic data must be analyzed and interpreted in the context of the individual patient’s pathology and inherent biologic variability. Certain data-driven analytical methods are currently being explored for smart monitoring of data streams from patients as a first tier automated detection system for clinical deterioration. As a prelude to human clinical trials, an empirical multivariate machine learning method called Similarity-Based Modeling (“SBM”), was tested in an In Silico experiment using data generated with the aid of a detailed computer simulator of human physiology (Quantitative Circulatory Physiology or “QCP”) which contains complex control systems with realistic integrated feedback loops. Methods. SBM is a kernel-based, multivariate machine learning method that that uses monitored clinical information to generate an empirical model of a patient’s physiologic state. This platform allows for the use of predictive analytic techniques to identify early changes in a patient’s condition that are indicative of a state of deterioration or instability. The integrity of the technique was tested through an In Silico experiment using QCP in which the output of computer simulations of a slowly evolving cardiac tamponade resulted in progressive state of cardiovascular decompensation. Simulator outputs for the variables under consideration were generated at a 2-min data rate (0.083Hz) with the tamponade introduced at a point 420 minutes into the simulation sequence. The functionality of the SBM predictive analytics methodology to identify clinical deterioration was compared to the thresholds used by conventional monitoring methods. Results. The SBM modeling method was found to closely track the normal physiologic variation as simulated by QCP. With the slow development of the tamponade, the SBM model are seen to disagree while the

Experimental testing of Mackay's model for functional antagonism in the isolated costo-uterus of the rat.

PubMed Central

Henry, P. J.; Lulich, K. M.; Paterson, J. W.

1985-01-01

Several key predictions of a recently developed model for functional antagonism (Mackay, 1981) were experimentally tested using the rat isolated costo-uterine preparation. In the presence of the functional antagonist fenoterol (Fen), the functional constants (KAF) for carbachol and oxotremorine (Oxo) were respectively 9.9 and 3.4 fold greater than their corresponding affinity constants (KA). According to Mackay's model for functional antagonism, the higher KAF/KA ratio for carbachol indicates that this cholinoceptor agonist has a greater efficacy than Oxo. This was confirmed by using conventional pharmacological methods. As predicted from the model of functional antagonism, the plot of KAF/KA-1 against the fraction of cholinoceptors not irreversibly blocked by phenoxybenzamine (Pbz) was linear for both carbachol and Oxo and the lines of best fit crossed the axes at a point not significantly different from the origin. The value of 4.6 for the relative efficacy of carbachol to Oxo estimated from functional antagonism studies was comparable to the value of 5.6 calculated using the method of irreversible antagonism proposed by Furchgott (1966). PMID:3840396

Interactions between callous unemotional behaviors and executive function in early childhood predict later socioemotional functioning

PubMed Central

Waller, Rebecca; Hyde, Luke W.; Baskin-Sommers, Arielle; Olson, Sheryl L.

2018-01-01

Callous unemotional (CU) behaviors are linked to aggression, behavior problems, and difficulties in peer relationships in children and adolescents. However, few studies have examined whether early childhood CU behaviors predict aggression or peer-rejection during late-childhood or potential moderation of this relationship by executive function. The current study examined whether the interaction of CU behaviors and executive function in early childhood predicted different forms of aggression in late-childhood, including proactive, reactive, and relational aggression, as well as how much children were liked by their peers. Data from cross-informant reports and multiple observational tasks were collected from a high-risk sample (N=240; female=118) at ages 3 and 10 years old. Parent reports of CU behaviors at age 3 predicted teacher reports of reactive, proactive, and relational aggression, as well as lower peer-liking at age 10. Moderation analysis showed that specifically at high levels of CU behaviors and low levels of observed executive function, children were reported by teachers as showing greater reactive and proactive aggression, and were less-liked by peers. Findings demonstrate that early childhood CU behaviors and executive function have unique main and interactive effects on both later aggression and lower peer-liking even when taking into account stability in behavior problems over time. By elucidating how CU behaviors and deficits in executive function potentiate each other during early childhood, we can better characterize the emergence of severe and persistent behavior and interpersonal difficulties across development. PMID:27418255

Which neuromuscular or cognitive test is the optimal screening tool to predict falls in frail community-dwelling older people?

PubMed

Shimada, Hiroyuki; Suzukawa, Megumi; Tiedemann, Anne; Kobayashi, Kumiko; Yoshida, Hideyo; Suzuki, Takao

2009-01-01

The use of falls risk screening tools may aid in targeting fall prevention interventions in older individuals most likely to benefit. To determine the optimal physical or cognitive test to screen for falls risk in frail older people. This prospective cohort study involved recruitment from 213 day-care centers in Japan. The feasibility study included 3,340 ambulatory individuals aged 65 years or older enrolled in the Tsukui Ordered Useful Care for Health (TOUCH) program. The external validation study included a subsample of 455 individuals who completed all tests. Physical tests included grip strength (GS), chair stand test (CST), one-leg standing test (OLS), functional reach test (FRT), tandem walking test (TWT), 6-meter walking speed at a comfortable pace (CWS) and at maximum pace (MWS), and timed up-and-go test (TUG). The mental status questionnaire (MSQ) was used to measure cognitive function. The incidence of falls during 1 year was investigated by self-report or an interview with the participant's family and care staff. The most practicable tests were the GS and MSQ, which could be administered to more than 90% of the participants regardless of the activities of daily living status. The FRT and TWT had lower feasibility than other lower limb function tests. During the 1-year retrospective analysis of falls, 99 (21.8%) of the 455 validation study participants had fallen at least once. Fallers showed significantly poorer performance than non-fallers in the OLS (p = 0.003), TWT (p = 0.001), CWS (p = 0.013), MWS (p = 0.007), and TUG (p = 0.011). The OLS, CWS, and MWS remained significantly associated with falls when performance cut-points were determined. Logistic regression analysis revealed that the TWT was a significant and independent, yet weak predictor of falls. A weighting system which considered feasibility and validity scored the CWS (at a cut-point of 0.7 m/s) as the best test to predict risk of falls. Clinical tests of neuromuscular function can predict

Tiltrotor Aeroacoustic Code (TRAC) Prediction Assessment and Initial Comparisons with Tram Test Data

NASA Technical Reports Server (NTRS)

Burley, Casey L.; Brooks, Thomas F.; Charles, Bruce D.; McCluer, Megan

1999-01-01

A prediction sensitivity assessment to inputs and blade modeling is presented for the TiltRotor Aeroacoustic Code (TRAC). For this study, the non-CFD prediction system option in TRAC is used. Here, the comprehensive rotorcraft code, CAMRAD.Mod1, coupled with the high-resolution sectional loads code HIRES, predicts unsteady blade loads to be used in the noise prediction code WOPWOP. The sensitivity of the predicted blade motions, blade airloads, wake geometry, and acoustics is examined with respect to rotor rpm, blade twist and chord, and to blade dynamic modeling. To accomplish this assessment, an interim input-deck for the TRAM test model and an input-deck for a reference test model are utilized in both rigid and elastic modes. Both of these test models are regarded as near scale models of the V-22 proprotor (tiltrotor). With basic TRAC sensitivities established, initial TRAC predictions are compared to results of an extensive test of an isolated model proprotor. The test was that of the TiltRotor Aeroacoustic Model (TRAM) conducted in the Duits-Nederlandse Windtunnel (DNW). Predictions are compared to measured noise for the proprotor operating over an extensive range of conditions. The variation of predictions demonstrates the great care that must be taken in defining the blade motion. However, even with this variability, the predictions using the different blade modeling successfully capture (bracket) the levels and trends of the noise for conditions ranging from descent to ascent.

Tiltrotor Aeroacoustic Code (TRAC) Prediction Assessment and Initial Comparisons With TRAM Test Data

NASA Technical Reports Server (NTRS)

Burley, Casey L.; Brooks, Thomas F.; Charles, Bruce D.; McCluer, Megan

1999-01-01

A prediction sensitivity assessment to inputs and blade modeling is presented for the TiltRotor Aeroacoustic Code (TRAC). For this study, the non-CFD prediction system option in TRAC is used. Here, the comprehensive rotorcraft code, CAMRAD.Mod 1, coupled with the high-resolution sectional loads code HIRES, predicts unsteady blade loads to be used in the noise prediction code WOPWOP. The sensitivity of the predicted blade motions, blade airloads, wake geometry, and acoustics is examined with respect to rotor rpm, blade twist and chord, and to blade dynamic modeling. To accomplish this assessment. an interim input-deck for the TRAM test model and an input-deck for a reference test model are utilized in both rigid and elastic modes. Both of these test models are regarded as near scale models of the V-22 proprotor (tiltrotor). With basic TRAC sensitivities established, initial TRAC predictions are compared to results of an extensive test of an isolated model proprotor. The test was that of the TiltRotor Aeroacoustic Model (TRAM) conducted in the Duits-Nederlandse Windtunnel (DNW). Predictions are compared to measured noise for the proprotor operating over an extensive range of conditions. The variation of predictions demonstrates the great care that must be taken in defining the blade motion. However, even with this variability, the predictions using the different blade modeling successfully capture (bracket) the levels and trends of the noise for conditions ranging from descent to ascent.

Nonparametric tests for equality of psychometric functions.

PubMed