Dehesh, Tania; Zare, Najaf; Ayatollahi, Seyyed Mohammad Taghi
2015-01-01
Background. Univariate meta-analysis (UM) procedure, as a technique that provides a single overall result, has become increasingly popular. Neglecting the existence of other concomitant covariates in the models leads to loss of treatment efficiency. Our aim was proposing four new approximation approaches for the covariance matrix of the coefficients, which is not readily available for the multivariate generalized least square (MGLS) method as a multivariate meta-analysis approach. Methods. We evaluated the efficiency of four new approaches including zero correlation (ZC), common correlation (CC), estimated correlation (EC), and multivariate multilevel correlation (MMC) on the estimation bias, mean square error (MSE), and 95% probability coverage of the confidence interval (CI) in the synthesis of Cox proportional hazard models coefficients in a simulation study. Result. Comparing the results of the simulation study on the MSE, bias, and CI of the estimated coefficients indicated that MMC approach was the most accurate procedure compared to EC, CC, and ZC procedures. The precision ranking of the four approaches according to all above settings was MMC ≥ EC ≥ CC ≥ ZC. Conclusion. This study highlights advantages of MGLS meta-analysis on UM approach. The results suggested the use of MMC procedure to overcome the lack of information for having a complete covariance matrix of the coefficients. PMID:26413142
Partial covariate adjusted regression
Şentürk, Damla; Nguyen, Danh V.
2008-01-01
Covariate adjusted regression (CAR) is a recently proposed adjustment method for regression analysis where both the response and predictors are not directly observed (Şentürk and Müller, 2005). The available data has been distorted by unknown functions of an observable confounding covariate. CAR provides consistent estimators for the coefficients of the regression between the variables of interest, adjusted for the confounder. We develop a broader class of partial covariate adjusted regression (PCAR) models to accommodate both distorted and undistorted (adjusted/unadjusted) predictors. The PCAR model allows for unadjusted predictors, such as age, gender and demographic variables, which are common in the analysis of biomedical and epidemiological data. The available estimation and inference procedures for CAR are shown to be invalid for the proposed PCAR model. We propose new estimators and develop new inference tools for the more general PCAR setting. In particular, we establish the asymptotic normality of the proposed estimators and propose consistent estimators of their asymptotic variances. Finite sample properties of the proposed estimators are investigated using simulation studies and the method is also illustrated with a Pima Indians diabetes data set. PMID:20126296
Agogo, George O; van der Voet, Hilko; Van't Veer, Pieter; van Eeuwijk, Fred A; Boshuizen, Hendriek C
2016-07-01
Dietary questionnaires are prone to measurement error, which bias the perceived association between dietary intake and risk of disease. Short-term measurements are required to adjust for the bias in the association. For foods that are not consumed daily, the short-term measurements are often characterized by excess zeroes. Via a simulation study, the performance of a two-part calibration model that was developed for a single-replicate study design was assessed by mimicking leafy vegetable intake reports from the multicenter European Prospective Investigation into Cancer and Nutrition (EPIC) study. In part I of the fitted two-part calibration model, a logistic distribution was assumed; in part II, a gamma distribution was assumed. The model was assessed with respect to the magnitude of the correlation between the consumption probability and the consumed amount (hereafter, cross-part correlation), the number and form of covariates in the calibration model, the percentage of zero response values, and the magnitude of the measurement error in the dietary intake. From the simulation study results, transforming the dietary variable in the regression calibration to an appropriate scale was found to be the most important factor for the model performance. Reducing the number of covariates in the model could be beneficial, but was not critical in large-sample studies. The performance was remarkably robust when fitting a one-part rather than a two-part model. The model performance was minimally affected by the cross-part correlation. PMID:27003183
Survival analysis of cervical cancer using stratified Cox regression
NASA Astrophysics Data System (ADS)
Purnami, S. W.; Inayati, K. D.; Sari, N. W. Wulan; Chosuvivatwong, V.; Sriplung, H.
2016-04-01
Cervical cancer is one of the mostly widely cancer cause of the women death in the world including Indonesia. Most cervical cancer patients come to the hospital already in an advanced stadium. As a result, the treatment of cervical cancer becomes more difficult and even can increase the death's risk. One of parameter that can be used to assess successfully of treatment is the probability of survival. This study raises the issue of cervical cancer survival patients at Dr. Soetomo Hospital using stratified Cox regression based on six factors such as age, stadium, treatment initiation, companion disease, complication, and anemia. Stratified Cox model is used because there is one independent variable that does not satisfy the proportional hazards assumption that is stadium. The results of the stratified Cox model show that the complication variable is significant factor which influent survival probability of cervical cancer patient. The obtained hazard ratio is 7.35. It means that cervical cancer patient who has complication is at risk of dying 7.35 times greater than patient who did not has complication. While the adjusted survival curves showed that stadium IV had the lowest probability of survival.
Simultaneous confidence bands for Cox regression from semiparametric random censorship.
Mondal, Shoubhik; Subramanian, Sundarraman
2016-01-01
Cox regression is combined with semiparametric random censorship models to construct simultaneous confidence bands (SCBs) for subject-specific survival curves. Simulation results are presented to compare the performance of the proposed SCBs with the SCBs that are based only on standard Cox. The new SCBs provide correct empirical coverage and are more informative. The proposed SCBs are illustrated with two real examples. An extension to handle missing censoring indicators is also outlined. PMID:25691289
Partial least squares Cox regression for genome-wide data.
Nygård, Ståle; Borgan, Ornulf; Lingjaerde, Ole Christian; Størvold, Hege Leite
2008-06-01
Most methods for survival prediction from high-dimensional genomic data combine the Cox proportional hazards model with some technique of dimension reduction, such as partial least squares regression (PLS). Applying PLS to the Cox model is not entirely straightforward, and multiple approaches have been proposed. The method of Park etal. (Bioinformatics 18(Suppl. 1):S120-S127, 2002) uses a reformulation of the Cox likelihood to a Poisson type likelihood, thereby enabling estimation by iteratively reweighted partial least squares for generalized linear models. We propose a modification of the method of Park et al. (2002) such that estimates of the baseline hazard and the gene effects are obtained in separate steps. The resulting method has several advantages over the method of Park et al. (2002) and other existing Cox PLS approaches, as it allows for estimation of survival probabilities for new patients, enables a less memory-demanding estimation procedure, and allows for incorporation of lower-dimensional non-genomic variables like disease grade and tumor thickness. We also propose to combine our Cox PLS method with an initial gene selection step in which genes are ordered by their Cox score and only the highest-ranking k% of the genes are retained, obtaining a so-called supervised partial least squares regression method. In simulations, both the unsupervised and the supervised version outperform other Cox PLS methods. PMID:18188699
Diagnostic Measures for the Cox Regression Model with Missing Covariates
Zhu, Hongtu; Ibrahim, Joseph G.; Chen, Ming-Hui
2015-01-01
Summary This paper investigates diagnostic measures for assessing the influence of observations and model misspecification in the presence of missing covariate data for the Cox regression model. Our diagnostics include case-deletion measures, conditional martingale residuals, and score residuals. The Q-distance is proposed to examine the effects of deleting individual observations on the estimates of finite-dimensional and infinite-dimensional parameters. Conditional martingale residuals are used to construct goodness of fit statistics for testing possible misspecification of the model assumptions. A resampling method is developed to approximate the p-values of the goodness of fit statistics. Simulation studies are conducted to evaluate our methods, and a real data set is analyzed to illustrate their use. PMID:26903666
Cox Regression Models with Functional Covariates for Survival Data
Gellar, Jonathan E.; Colantuoni, Elizabeth; Needham, Dale M.; Crainiceanu, Ciprian M.
2015-01-01
We extend the Cox proportional hazards model to cases when the exposure is a densely sampled functional process, measured at baseline. The fundamental idea is to combine penalized signal regression with methods developed for mixed effects proportional hazards models. The model is fit by maximizing the penalized partial likelihood, with smoothing parameters estimated by a likelihood-based criterion such as AIC or EPIC. The model may be extended to allow for multiple functional predictors, time varying coefficients, and missing or unequally-spaced data. Methods were inspired by and applied to a study of the association between time to death after hospital discharge and daily measures of disease severity collected in the intensive care unit, among survivors of acute respiratory distress syndrome. PMID:26441487
ERIC Educational Resources Information Center
Chen, Chau-Kuang
2005-01-01
Logistic and Cox regression methods are practical tools used to model the relationships between certain student learning outcomes and their relevant explanatory variables. The logistic regression model fits an S-shaped curve into a binary outcome with data points of zero and one. The Cox regression model allows investigators to study the duration…
Factors Associated with Methadone Treatment Duration: A Cox Regression Analysis
Peng, Ching-Yi; Chao, En; Lee, Tony Szu-Hsien
2015-01-01
This study examined retention rates and associated predictors of methadone maintenance treatment (MMT) duration among 128 newly admitted patients in Taiwan. A semi-structured questionnaire was used to obtain demographic and drug use history. Daily records of methadone taken and test results for HIV, HCV, and morphine toxicology were taken from a computerized medical registry. Cox regression analyses were performed to examine factors associated with MMT duration. MMT retention rates were 80.5%, 68.8%, 53.9%, and 41.4% for 3, 6, 12, and 18 months, respectively. Excluding 38 patients incarcerated during the study period, retention rates were 81.1%, 73.3%, 61.1%, and 48.9% for 3 months, 6 months, 12 months, and 18 months, respectively. No participant seroconverted to HIV and 1 died during the 18-months follow-up. Results showed that being female, imprisonment, a longer distance from house to clinic, having a lower methadone dose after 30 days, being HCV positive, and in the New Taipei city program predicted early patient dropout. The findings suggest favorable MMT outcomes of HIV seroincidence and mortality. Results indicate that the need to minimize travel distance and to provide programs that meet women’s requirements justify expansion of MMT clinics in Taiwan. PMID:25875531
Box–Cox Transformation and Random Regression Models for Fecal egg Count Data
da Silva, Marcos Vinícius Gualberto Barbosa; Van Tassell, Curtis P.; Sonstegard, Tad S.; Cobuci, Jaime Araujo; Gasbarre, Louis C.
2012-01-01
Accurate genetic evaluation of livestock is based on appropriate modeling of phenotypic measurements. In ruminants, fecal egg count (FEC) is commonly used to measure resistance to nematodes. FEC values are not normally distributed and logarithmic transformations have been used in an effort to achieve normality before analysis. However, the transformed data are often still not normally distributed, especially when data are extremely skewed. A series of repeated FEC measurements may provide information about the population dynamics of a group or individual. A total of 6375 FEC measures were obtained for 410 animals between 1992 and 2003 from the Beltsville Agricultural Research Center Angus herd. Original data were transformed using an extension of the Box–Cox transformation to approach normality and to estimate (co)variance components. We also proposed using random regression models (RRM) for genetic and non-genetic studies of FEC. Phenotypes were analyzed using RRM and restricted maximum likelihood. Within the different orders of Legendre polynomials used, those with more parameters (order 4) adjusted FEC data best. Results indicated that the transformation of FEC data utilizing the Box–Cox transformation family was effective in reducing the skewness and kurtosis, and dramatically increased estimates of heritability, and measurements of FEC obtained in the period between 12 and 26 weeks in a 26-week experimental challenge period are genetically correlated. PMID:22303406
Tosteson, Tor D.; Morden, Nancy E.; Stukel, Therese A.; O'Malley, A. James
2014-01-01
The estimation of treatment effects is one of the primary goals of statistics in medicine. Estimation based on observational studies is subject to confounding. Statistical methods for controlling bias due to confounding include regression adjustment, propensity scores and inverse probability weighted estimators. These methods require that all confounders are recorded in the data. The method of instrumental variables (IVs) can eliminate bias in observational studies even in the absence of information on confounders. We propose a method for integrating IVs within the framework of Cox's proportional hazards model and demonstrate the conditions under which it recovers the causal effect of treatment. The methodology is based on the approximate orthogonality of an instrument with unobserved confounders among those at risk. We derive an estimator as the solution to an estimating equation that resembles the score equation of the partial likelihood in much the same way as the traditional IV estimator resembles the normal equations. To justify this IV estimator for a Cox model we perform simulations to evaluate its operating characteristics. Finally, we apply the estimator to an observational study of the effect of coronary catheterization on survival. PMID:25506259
Weather adjustment using seemingly unrelated regression
Noll, T.A.
1995-05-01
Seemingly unrelated regression (SUR) is a system estimation technique that accounts for time-contemporaneous correlation between individual equations within a system of equations. SUR is suited to weather adjustment estimations when the estimation is: (1) composed of a system of equations and (2) the system of equations represents either different weather stations, different sales sectors or a combination of different weather stations and different sales sectors. SUR utilizes the cross-equation error values to develop more accurate estimates of the system coefficients than are obtained using ordinary least-squares (OLS) estimation. SUR estimates can be generated using a variety of statistical software packages including MicroTSP and SAS.
Mortality Prediction in ICUs Using A Novel Time-Slicing Cox Regression Method
Wang, Yuan; Chen, Wenlin; Heard, Kevin; Kollef, Marin H.; Bailey, Thomas C.; Cui, Zhicheng; He, Yujie; Lu, Chenyang; Chen, Yixin
2015-01-01
Over the last few decades, machine learning and data mining have been increasingly used for clinical prediction in ICUs. However, there is still a huge gap in making full use of the time-series data generated from ICUs. Aiming at filling this gap, we propose a novel approach entitled Time Slicing Cox regression (TS-Cox), which extends the classical Cox regression into a classification method on multi-dimensional time-series. Unlike traditional classifiers such as logistic regression and support vector machines, our model not only incorporates the discriminative features derived from the time-series, but also naturally exploits the temporal orders of these features based on a Cox-like function. Empirical evaluation on MIMIC-II database demonstrates the efficacy of the TS-Cox model. Our TS-Cox model outperforms all other baseline models by a good margin in terms of AUC_PR, sensitivity and PPV, which indicates that TS-Cox may be a promising tool for mortality prediction in ICUs. PMID:26958269
Iuliano, Antonella; Occhipinti, Annalisa; Angelini, Claudia; De Feis, Italia; Lió, Pietro
2016-01-01
International initiatives such as the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) are collecting multiple datasets at different genome-scales with the aim of identifying novel cancer biomarkers and predicting survival of patients. To analyze such data, several statistical methods have been applied, among them Cox regression models. Although these models provide a good statistical framework to analyze omic data, there is still a lack of studies that illustrate advantages and drawbacks in integrating biological information and selecting groups of biomarkers. In fact, classical Cox regression algorithms focus on the selection of a single biomarker, without taking into account the strong correlation between genes. Even though network-based Cox regression algorithms overcome such drawbacks, such network-based approaches are less widely used within the life science community. In this article, we aim to provide a clear methodological framework on the use of such approaches in order to turn cancer research results into clinical applications. Therefore, we first discuss the rationale and the practical usage of three recently proposed network-based Cox regression algorithms (i.e., Net-Cox, AdaLnet, and fastcox). Then, we show how to combine existing biological knowledge and available data with such algorithms to identify networks of cancer biomarkers and to estimate survival of patients. Finally, we describe in detail a new permutation-based approach to better validate the significance of the selection in terms of cancer gene signatures and pathway/networks identification. We illustrate the proposed methodology by means of both simulations and real case studies. Overall, the aim of our work is two-fold. Firstly, to show how network-based Cox regression models can be used to integrate biological knowledge (e.g., multi-omics data) for the analysis of survival data. Secondly, to provide a clear methodological and computational approach for
Xu, Haoming; Moni, Mohammad Ali; Liò, Pietro
2015-12-01
In cancer genomics, gene expression levels provide important molecular signatures for all types of cancer, and this could be very useful for predicting the survival of cancer patients. However, the main challenge of gene expression data analysis is high dimensionality, and microarray is characterised by few number of samples with large number of genes. To overcome this problem, a variety of penalised Cox proportional hazard models have been proposed. We introduce a novel network regularised Cox proportional hazard model and a novel multiplex network model to measure the disease comorbidities and to predict survival of the cancer patient. Our methods are applied to analyse seven microarray cancer gene expression datasets: breast cancer, ovarian cancer, lung cancer, liver cancer, renal cancer and osteosarcoma. Firstly, we applied a principal component analysis to reduce the dimensionality of original gene expression data. Secondly, we applied a network regularised Cox regression model on the reduced gene expression datasets. By using normalised mutual information method and multiplex network model, we predict the comorbidities for the liver cancer based on the integration of diverse set of omics and clinical data, and we find the diseasome associations (disease-gene association) among different cancers based on the identified common significant genes. Finally, we evaluated the precision of the approach with respect to the accuracy of survival prediction using ROC curves. We report that colon cancer, liver cancer and renal cancer share the CXCL5 gene, and breast cancer, ovarian cancer and renal cancer share the CCND2 gene. Our methods are useful to predict survival of the patient and disease comorbidities more accurately and helpful for improvement of the care of patients with comorbidity. Software in Matlab and R is available on our GitHub page: https://github.com/ssnhcom/NetworkRegularisedCox.git. PMID:26611766
Pathway-gene identification for pancreatic cancer survival via doubly regularized Cox regression
2014-01-01
Background Recent global genomic analyses identified 69 gene sets and 12 core signaling pathways genetically altered in pancreatic cancer, which is a highly malignant disease. A comprehensive understanding of the genetic signatures and signaling pathways that are directly correlated to pancreatic cancer survival will help cancer researchers to develop effective multi-gene targeted, personalized therapies for the pancreatic cancer patients at different stages. A previous work that applied a LASSO penalized regression method, which only considered individual genetic effects, identified 12 genes associated with pancreatic cancer survival. Results In this work, we integrate pathway information into pancreatic cancer survival analysis. We introduce and apply a doubly regularized Cox regression model to identify both genes and signaling pathways related to pancreatic cancer survival. Conclusions Four signaling pathways, including Ion transport, immune phagocytosis, TGFβ (spermatogenesis), regulation of DNA-dependent transcription pathways, and 15 genes within the four pathways are identified and verified to be directly correlated to pancreatic cancer survival. Our findings can help cancer researchers design new strategies for the early detection and diagnosis of pancreatic cancer. PMID:24565114
Vatcheva, KP; Lee, M; McCormick, JB; Rahbar, MH
2016-01-01
Objective To demonstrate the adverse impact of ignoring statistical interactions in regression models used in epidemiologic studies. Study design and setting Based on different scenarios that involved known values for coefficient of the interaction term in Cox regression models we generated 1000 samples of size 600 each. The simulated samples and a real life data set from the Cameron County Hispanic Cohort were used to evaluate the effect of ignoring statistical interactions in these models. Results Compared to correctly specified Cox regression models with interaction terms, misspecified models without interaction terms resulted in up to 8.95 fold bias in estimated regression coefficients. Whereas when data were generated from a perfect additive Cox proportional hazards regression model the inclusion of the interaction between the two covariates resulted in only 2% estimated bias in main effect regression coefficients estimates, but did not alter the main findings of no significant interactions. Conclusions When the effects are synergic, the failure to account for an interaction effect could lead to bias and misinterpretation of the results, and in some instances to incorrect policy decisions. Best practices in regression analysis must include identification of interactions, including for analysis of data from epidemiologic studies.
Nie, Z Q; Ou, Y Q; Zhuang, J; Qu, Y J; Mai, J Z; Chen, J M; Liu, X Q
2016-05-10
Conditional logistic regression analysis and unconditional logistic regression analysis are commonly used in case control study, but Cox proportional hazard model is often used in survival data analysis. Most literature only refer to main effect model, however, generalized linear model differs from general linear model, and the interaction was composed of multiplicative interaction and additive interaction. The former is only statistical significant, but the latter has biological significance. In this paper, macros was written by using SAS 9.4 and the contrast ratio, attributable proportion due to interaction and synergy index were calculated while calculating the items of logistic and Cox regression interactions, and the confidence intervals of Wald, delta and profile likelihood were used to evaluate additive interaction for the reference in big data analysis in clinical epidemiology and in analysis of genetic multiplicative and additive interactions. PMID:27188374
Lee, Eunjee; Zhu, Hongtu; Kong, Dehan; Wang, Yalin; Giovanello, Kelly Sullivan; Ibrahim, Joseph G
2015-01-01
The aim of this paper is to develop a Bayesian functional linear Cox regression model (BFLCRM) with both functional and scalar covariates. This new development is motivated by establishing the likelihood of conversion to Alzheimer’s disease (AD) in 346 patients with mild cognitive impairment (MCI) enrolled in the Alzheimer’s Disease Neuroimaging Initiative 1 (ADNI-1) and the early markers of conversion. These 346 MCI patients were followed over 48 months, with 161 MCI participants progressing to AD at 48 months. The functional linear Cox regression model was used to establish that functional covariates including hippocampus surface morphology and scalar covariates including brain MRI volumes, cognitive performance (ADAS-Cog), and APOE status can accurately predict time to onset of AD. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. A simulation study is performed to evaluate the finite sample performance of BFLCRM. PMID:26900412
Estimation of adjusted rate differences using additive negative binomial regression.
Donoghoe, Mark W; Marschner, Ian C
2016-08-15
Rate differences are an important effect measure in biostatistics and provide an alternative perspective to rate ratios. When the data are event counts observed during an exposure period, adjusted rate differences may be estimated using an identity-link Poisson generalised linear model, also known as additive Poisson regression. A problem with this approach is that the assumption of equality of mean and variance rarely holds in real data, which often show overdispersion. An additive negative binomial model is the natural alternative to account for this; however, standard model-fitting methods are often unable to cope with the constrained parameter space arising from the non-negativity restrictions of the additive model. In this paper, we propose a novel solution to this problem using a variant of the expectation-conditional maximisation-either algorithm. Our method provides a reliable way to fit an additive negative binomial regression model and also permits flexible generalisations using semi-parametric regression functions. We illustrate the method using a placebo-controlled clinical trial of fenofibrate treatment in patients with type II diabetes, where the outcome is the number of laser therapy courses administered to treat diabetic retinopathy. An R package is available that implements the proposed method. Copyright © 2016 John Wiley & Sons, Ltd. PMID:27073156
NASA Technical Reports Server (NTRS)
Kattan, Michael W.; Hess, Kenneth R.; Kattan, Michael W.
1998-01-01
New computationally intensive tools for medical survival analyses include recursive partitioning (also called CART) and artificial neural networks. A challenge that remains is to better understand the behavior of these techniques in effort to know when they will be effective tools. Theoretically they may overcome limitations of the traditional multivariable survival technique, the Cox proportional hazards regression model. Experiments were designed to test whether the new tools would, in practice, overcome these limitations. Two datasets in which theory suggests CART and the neural network should outperform the Cox model were selected. The first was a published leukemia dataset manipulated to have a strong interaction that CART should detect. The second was a published cirrhosis dataset with pronounced nonlinear effects that a neural network should fit. Repeated sampling of 50 training and testing subsets was applied to each technique. The concordance index C was calculated as a measure of predictive accuracy by each technique on the testing dataset. In the interaction dataset, CART outperformed Cox (P less than 0.05) with a C improvement of 0.1 (95% Cl, 0.08 to 0.12). In the nonlinear dataset, the neural network outperformed the Cox model (P less than 0.05), but by a very slight amount (0.015). As predicted by theory, CART and the neural network were able to overcome limitations of the Cox model. Experiments like these are important to increase our understanding of when one of these new techniques will outperform the standard Cox model. Further research is necessary to predict which technique will do best a priori and to assess the magnitude of superiority.
Devarajan, Karthik; Ebrahimi, Nader
2010-01-01
The assumption of proportional hazards (PH) fundamental to the Cox PH model sometimes may not hold in practice. In this paper, we propose a generalization of the Cox PH model in terms of the cumulative hazard function taking a form similar to the Cox PH model, with the extension that the baseline cumulative hazard function is raised to a power function. Our model allows for interaction between covariates and the baseline hazard and it also includes, for the two sample problem, the case of two Weibull distributions and two extreme value distributions differing in both scale and shape parameters. The partial likelihood approach can not be applied here to estimate the model parameters. We use the full likelihood approach via a cubic B-spline approximation for the baseline hazard to estimate the model parameters. A semi-automatic procedure for knot selection based on Akaike’s Information Criterion is developed. We illustrate the applicability of our approach using real-life data. PMID:21076652
Devarajan, Karthik; Ebrahimi, Nader
2011-01-01
The assumption of proportional hazards (PH) fundamental to the Cox PH model sometimes may not hold in practice. In this paper, we propose a generalization of the Cox PH model in terms of the cumulative hazard function taking a form similar to the Cox PH model, with the extension that the baseline cumulative hazard function is raised to a power function. Our model allows for interaction between covariates and the baseline hazard and it also includes, for the two sample problem, the case of two Weibull distributions and two extreme value distributions differing in both scale and shape parameters. The partial likelihood approach can not be applied here to estimate the model parameters. We use the full likelihood approach via a cubic B-spline approximation for the baseline hazard to estimate the model parameters. A semi-automatic procedure for knot selection based on Akaike's Information Criterion is developed. We illustrate the applicability of our approach using real-life data. PMID:21076652
Including network knowledge into Cox regression models for biomarker signature discovery.
Fröhlich, Holger
2014-03-01
Discovery of prognostic and diagnostic biomarker gene signatures for diseases, such as cancer, is seen as a major step toward a better personalized medicine. During the last decade various methods have been proposed for that purpose. However, one important obstacle for making gene signatures a standard tool in clinical diagnosis is the typical low reproducibility of these signatures combined with the difficulty to achieve a clear biological interpretation. For that purpose in the last years there has been a growing interest in approaches that try to integrate information from molecular interaction networks. Most of these methods focus on classification problems, that is learn a model from data that discriminates patients into distinct clinical groups. Far less has been published on approaches that predict a patient's event risk. In this paper, we investigate eight methods that integrate network information into multivariable Cox proportional hazard models for risk prediction in breast cancer. We compare the prediction performance of our tested algorithms via cross-validation as well as across different datasets. In addition, we highlight the stability and interpretability of obtained gene signatures. In conclusion, we find GeneRank-based filtering to be a simple, computationally cheap and highly predictive technique to integrate network information into event time prediction models. Signatures derived via this method are highly reproducible. PMID:24430933
Assessing Longitudinal Change: Adjustment for Regression to the Mean Effects
ERIC Educational Resources Information Center
Rocconi, Louis M.; Ethington, Corinna A.
2009-01-01
Pascarella (J Coll Stud Dev 47:508-520, 2006) has called for an increase in use of longitudinal data with pretest-posttest design when studying effects on college students. However, such designs that use multiple measures to document change are vulnerable to an important threat to internal validity, regression to the mean. Herein, we discuss a…
Procedures for adjusting regional regression models of urban-runoff quality using local data
Hoos, Anne B.; Lizarraga, Joy S.
1996-01-01
Statistical operations termed model-adjustment procedures can be used to incorporate local data into existing regression modes to improve the predication of urban-runoff quality. Each procedure is a form of regression analysis in which the local data base is used as a calibration data set; the resulting adjusted regression models can then be used to predict storm-runoff quality at unmonitored sites. Statistical tests of the calibration data set guide selection among proposed procedures.
Coercively Adjusted Auto Regression Model for Forecasting in Epilepsy EEG
Kim, Sun-Hee; Faloutsos, Christos; Yang, Hyung-Jeong
2013-01-01
Recently, data with complex characteristics such as epilepsy electroencephalography (EEG) time series has emerged. Epilepsy EEG data has special characteristics including nonlinearity, nonnormality, and nonperiodicity. Therefore, it is important to find a suitable forecasting method that covers these special characteristics. In this paper, we propose a coercively adjusted autoregression (CA-AR) method that forecasts future values from a multivariable epilepsy EEG time series. We use the technique of random coefficients, which forcefully adjusts the coefficients with −1 and 1. The fractal dimension is used to determine the order of the CA-AR model. We applied the CA-AR method reflecting special characteristics of data to forecast the future value of epilepsy EEG data. Experimental results show that when compared to previous methods, the proposed method can forecast faster and accurately. PMID:23710252
Lee, Paul H.
2016-01-01
Healthy adults are advised to perform at least 150 min of moderate-intensity physical activity weekly, but this advice is based on studies using self-reports of questionable validity. This study examined the dose-response relationship of accelerometer-measured physical activity and sedentary behaviors on all-cause mortality using segmented Cox regression to empirically determine the break-points of the dose-response relationship. Data from 7006 adult participants aged 18 or above in the National Health and Nutrition Examination Survey waves 2003–2004 and 2005–2006 were included in the analysis and linked with death certificate data using a probabilistic matching approach in the National Death Index through December 31, 2011. Physical activity and sedentary behavior were measured using ActiGraph model 7164 accelerometer over the right hip for 7 consecutive days. Each minute with accelerometer count <100; 1952–5724; and ≥5725 were classified as sedentary, moderate-intensity physical activity, and vigorous-intensity physical activity, respectively. Segmented Cox regression was used to estimate the hazard ratio (HR) of time spent in sedentary behaviors, moderate-intensity physical activity, and vigorous-intensity physical activity and all-cause mortality, adjusted for demographic characteristics, health behaviors, and health conditions. Data were analyzed in 2016. During 47,119 person-year of follow-up, 608 deaths occurred. Each additional hour per day of sedentary behaviors was associated with a HR of 1.15 (95% CI 1.01, 1.31) among participants who spend at least 10.9 h per day on sedentary behaviors, and each additional minute per day spent on moderate-intensity physical activity was associated with a HR of 0.94 (95% CI 0.91, 0.96) among participants with daily moderate-intensity physical activity ≤14.1 min. Associations of moderate physical activity and sedentary behaviors on all-cause mortality were independent of each other. To conclude, evidence from
Adjustment of regional regression equations for urban storm-runoff quality using at-site data
Barks, C.S.
1996-01-01
Regional regression equations have been developed to estimate urban storm-runoff loads and mean concentrations using a national data base. Four statistical methods using at-site data to adjust the regional equation predictions were developed to provide better local estimates. The four adjustment procedures are a single-factor adjustment, a regression of the observed data against the predicted values, a regression of the observed values against the predicted values and additional local independent variables, and a weighted combination of a local regression with the regional prediction. Data collected at five representative storm-runoff sites during 22 storms in Little Rock, Arkansas, were used to verify, and, when appropriate, adjust the regional regression equation predictions. Comparison of observed values of stormrunoff loads and mean concentrations to the predicted values from the regional regression equations for nine constituents (chemical oxygen demand, suspended solids, total nitrogen as N, total ammonia plus organic nitrogen as N, total phosphorus as P, dissolved phosphorus as P, total recoverable copper, total recoverable lead, and total recoverable zinc) showed large prediction errors ranging from 63 percent to more than several thousand percent. Prediction errors for 6 of the 18 regional regression equations were less than 100 percent and could be considered reasonable for water-quality prediction equations. The regression adjustment procedure was used to adjust five of the regional equation predictions to improve the predictive accuracy. For seven of the regional equations the observed and the predicted values are not significantly correlated. Thus neither the unadjusted regional equations nor any of the adjustments were appropriate. The mean of the observed values was used as a simple estimator when the regional equation predictions and adjusted predictions were not appropriate.
Ternès, Nils; Rotolo, Federico; Michiels, Stefan
2016-07-10
Correct selection of prognostic biomarkers among multiple candidates is becoming increasingly challenging as the dimensionality of biological data becomes higher. Therefore, minimizing the false discovery rate (FDR) is of primary importance, while a low false negative rate (FNR) is a complementary measure. The lasso is a popular selection method in Cox regression, but its results depend heavily on the penalty parameter λ. Usually, λ is chosen using maximum cross-validated log-likelihood (max-cvl). However, this method has often a very high FDR. We review methods for a more conservative choice of λ. We propose an empirical extension of the cvl by adding a penalization term, which trades off between the goodness-of-fit and the parsimony of the model, leading to the selection of fewer biomarkers and, as we show, to the reduction of the FDR without large increase in FNR. We conducted a simulation study considering null and moderately sparse alternative scenarios and compared our approach with the standard lasso and 10 other competitors: Akaike information criterion (AIC), corrected AIC, Bayesian information criterion (BIC), extended BIC, Hannan and Quinn information criterion (HQIC), risk information criterion (RIC), one-standard-error rule, adaptive lasso, stability selection, and percentile lasso. Our extension achieved the best compromise across all the scenarios between a reduction of the FDR and a limited raise of the FNR, followed by the AIC, the RIC, and the adaptive lasso, which performed well in some settings. We illustrate the methods using gene expression data of 523 breast cancer patients. In conclusion, we propose to apply our extension to the lasso whenever a stringent FDR with a limited FNR is targeted. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26970107
Khosravi, Bahareh; Pourahmad, Saeedeh; Bahreini, Amin; Nikeghbalian, Saman; Mehrdad, Goli
2015-01-01
Background: Transplantation is the only treatment for patients with liver failure. Since the therapy imposes high expenses to the patients and community, identification of effective factors on survival of such patients after transplantation is valuable. Objectives: The current study attempted to model the survival of patients (two years old and above) after liver transplantation using neural network and Cox Proportional Hazards (Cox PH) regression models. The event is defined as death due to complications of liver transplantation. Patients and Methods: In a historical cohort study, the clinical findings of 1168 patients who underwent liver transplant surgery (from March 2008 to march 2013) at Shiraz Namazee Hospital Organ Transplantation Center, Shiraz, Southern Iran, were used. To model the one to five years survival of such patients, Cox PH regression model accompanied by three layers feed forward artificial neural network (ANN) method were applied on data separately and their prediction accuracy was compared using the area under the receiver operating characteristic curve (ROC). Furthermore, Kaplan-Meier method was used to estimate the survival probabilities in different years. Results: The estimated survival probability of one to five years for the patients were 91%, 89%, 85%, 84%, and 83%, respectively. The areas under the ROC were 86.4% and 80.7% for ANN and Cox PH models, respectively. In addition, the accuracy of prediction rate for ANN and Cox PH methods was equally 92.73%. Conclusions: The present study detected more accurate results for ANN method compared to those of Cox PH model to analyze the survival of patients with liver transplantation. Furthermore, the order of effective factors in patients’ survival after transplantation was clinically more acceptable. The large dataset with a few missing data was the advantage of this study, the fact which makes the results more reliable. PMID:26500682
Comparison of the Properties of Regression and Categorical Risk-Adjustment Models
Averill, Richard F.; Muldoon, John H.; Hughes, John S.
2016-01-01
Clinical risk-adjustment, the ability to standardize the comparison of individuals with different health needs, is based upon 2 main alternative approaches: regression models and clinical categorical models. In this article, we examine the impact of the differences in the way these models are constructed on end user applications. PMID:26945302
ERIC Educational Resources Information Center
Olejnik, Stephen; Mills, Jamie; Keselman, Harvey
2000-01-01
Evaluated the use of Mallow's C(p) and Wherry's adjusted R squared (R. Wherry, 1931) statistics to select a final model from a pool of model solutions using computer generated data. Neither statistic identified the underlying regression model any better than, and usually less well than, the stepwise selection method, which itself was poor for…
Procedures for adjusting regional regression models of urban-runoff quality using local data
Hoos, A.B.; Sisolak, J.K.
1993-01-01
Statistical operations termed model-adjustment procedures (MAP?s) can be used to incorporate local data into existing regression models to improve the prediction of urban-runoff quality. Each MAP is a form of regression analysis in which the local data base is used as a calibration data set. Regression coefficients are determined from the local data base, and the resulting `adjusted? regression models can then be used to predict storm-runoff quality at unmonitored sites. The response variable in the regression analyses is the observed load or mean concentration of a constituent in storm runoff for a single storm. The set of explanatory variables used in the regression analyses is different for each MAP, but always includes the predicted value of load or mean concentration from a regional regression model. The four MAP?s examined in this study were: single-factor regression against the regional model prediction, P, (termed MAP-lF-P), regression against P,, (termed MAP-R-P), regression against P, and additional local variables (termed MAP-R-P+nV), and a weighted combination of P, and a local-regression prediction (termed MAP-W). The procedures were tested by means of split-sample analysis, using data from three cities included in the Nationwide Urban Runoff Program: Denver, Colorado; Bellevue, Washington; and Knoxville, Tennessee. The MAP that provided the greatest predictive accuracy for the verification data set differed among the three test data bases and among model types (MAP-W for Denver and Knoxville, MAP-lF-P and MAP-R-P for Bellevue load models, and MAP-R-P+nV for Bellevue concentration models) and, in many cases, was not clearly indicated by the values of standard error of estimate for the calibration data set. A scheme to guide MAP selection, based on exploratory data analysis of the calibration data set, is presented and tested. The MAP?s were tested for sensitivity to the size of a calibration data set. As expected, predictive accuracy of all MAP?s for
Algamal, Zakariya Yahya; Lee, Muhammad Hisyam
2015-12-01
Cancer classification and gene selection in high-dimensional data have been popular research topics in genetics and molecular biology. Recently, adaptive regularized logistic regression using the elastic net regularization, which is called the adaptive elastic net, has been successfully applied in high-dimensional cancer classification to tackle both estimating the gene coefficients and performing gene selection simultaneously. The adaptive elastic net originally used elastic net estimates as the initial weight, however, using this weight may not be preferable for certain reasons: First, the elastic net estimator is biased in selecting genes. Second, it does not perform well when the pairwise correlations between variables are not high. Adjusted adaptive regularized logistic regression (AAElastic) is proposed to address these issues and encourage grouping effects simultaneously. The real data results indicate that AAElastic is significantly consistent in selecting genes compared to the other three competitor regularization methods. Additionally, the classification performance of AAElastic is comparable to the adaptive elastic net and better than other regularization methods. Thus, we can conclude that AAElastic is a reliable adaptive regularized logistic regression method in the field of high-dimensional cancer classification. PMID:26520484
Wong, May C M; Lam, K F; Lo, Edward C M
2006-02-15
In some controlled clinical trials in dental research, multiple failure time data from the same patient are frequently observed that result in clustered multiple failure time. Moreover, the treatments are often delivered by more than one operator and thus the multiple failure times are clustered according to a multilevel structure when the operator effects are assumed to be random. In practice, it is often too expensive or even impossible to monitor the study subjects continuously, but they are examined periodically at some regular pre-scheduled visits. Hence, discrete or grouped clustered failure time data are collected. The aim of this paper is to illustrate the use of the Monte Carlo Markov chain (MCMC) approach and non-informative prior in a Bayesian framework to mimic the maximum likelihood (ML) estimation in a frequentist approach in multilevel modelling of clustered grouped survival data. A three-level model with additive variance components model for the random effects is considered in this paper. Both the grouped proportional hazards model and the dynamic logistic regression model are used. The approximate intra-cluster correlation of the log failure times can be estimated when the grouped proportional hazards model is used. The statistical package WinBUGS is adopted to estimate the parameter of interest based on the MCMC method. The models and method are applied to a data set obtained from a prospective clinical study on a cohort of Chinese school children that atraumatic restorative treatment (ART) restorations were placed on permanent teeth with carious lesions. Altogether 284 ART restorations were placed by five dentists and clinical status of the ART restorations was evaluated annually for 6 years after placement, thus clustered grouped failure times of the restorations were recorded. Results based on the grouped proportional hazards model revealed that clustering effect among the log failure times of the different restorations from the same child was
Kleinman, Lawrence C; Norton, Edward C
2009-01-01
Objective To develop and validate a general method (called regression risk analysis) to estimate adjusted risk measures from logistic and other nonlinear multiple regression models. We show how to estimate standard errors for these estimates. These measures could supplant various approximations (e.g., adjusted odds ratio [AOR]) that may diverge, especially when outcomes are common. Study Design Regression risk analysis estimates were compared with internal standards as well as with Mantel–Haenszel estimates, Poisson and log-binomial regressions, and a widely used (but flawed) equation to calculate adjusted risk ratios (ARR) from AOR. Data Collection Data sets produced using Monte Carlo simulations. Principal Findings Regression risk analysis accurately estimates ARR and differences directly from multiple regression models, even when confounders are continuous, distributions are skewed, outcomes are common, and effect size is large. It is statistically sound and intuitive, and has properties favoring it over other methods in many cases. Conclusions Regression risk analysis should be the new standard for presenting findings from multiple regression analysis of dichotomous outcomes for cross-sectional, cohort, and population-based case–control studies, particularly when outcomes are common or effect size is large. PMID:18793213
2014-01-01
Background Large-scale public health interventions with rapid scale-up are increasingly being implemented worldwide. Such implementation allows for a large target population to be reached in a short period of time. But when the time comes to investigate the effectiveness of these interventions, the rapid scale-up creates several methodological challenges, such as the lack of baseline data and the absence of control groups. One example of such an intervention is Avahan, the India HIV/AIDS initiative of the Bill & Melinda Gates Foundation. One question of interest is the effect of Avahan on condom use by female sex workers with their clients. By retrospectively reconstructing condom use and sex work history from survey data, it is possible to estimate how condom use rates evolve over time. However formal inference about how this rate changes at a given point in calendar time remains challenging. Methods We propose a new statistical procedure based on a mixture of binomial regression and Cox regression. We compare this new method to an existing approach based on generalized estimating equations through simulations and application to Indian data. Results Both methods are unbiased, but the proposed method is more powerful than the existing method, especially when initial condom use is high. When applied to the Indian data, the new method mostly agrees with the existing method, but seems to have corrected some implausible results of the latter in a few districts. We also show how the new method can be used to analyze the data of all districts combined. Conclusions The use of both methods can be recommended for exploratory data analysis. However for formal statistical inference, the new method has better power. PMID:24397563
Giganti, Mark J.; Luz, Paula M.; Caro-Vega, Yanink; Cesar, Carina; Padgett, Denis; Koenig, Serena; Echevarria, Juan; McGowan, Catherine C.; Shepherd, Bryan E.
2015-01-01
Abstract Many studies of HIV/AIDS aggregate data from multiple cohorts to improve power and generalizability. There are several analysis approaches to account for cross-cohort heterogeneity; we assessed how different approaches can impact results from an HIV/AIDS study investigating predictors of mortality. Using data from 13,658 HIV-infected patients starting antiretroviral therapy from seven Latin American and Caribbean cohorts, we illustrate the assumptions of seven readily implementable approaches to account for across cohort heterogeneity with Cox proportional hazards models, and we compare hazard ratio estimates across approaches. As a sensitivity analysis, we modify cohort membership to generate specific heterogeneity conditions. Hazard ratio estimates varied slightly between the seven analysis approaches, but differences were not clinically meaningful. Adjusted hazard ratio estimates for the association between AIDS at treatment initiation and death varied from 2.00 to 2.20 across approaches that accounted for heterogeneity; the adjusted hazard ratio was estimated as 1.73 in analyses that ignored across cohort heterogeneity. In sensitivity analyses with more extreme heterogeneity, we noted a slightly greater distinction between approaches. Despite substantial heterogeneity between cohorts, the impact of the specific approach to account for heterogeneity was minimal in our case study. Our results suggest that it is important to account for across cohort heterogeneity in analyses, but that the specific technique for addressing heterogeneity may be less important. Because of their flexibility in accounting for cohort heterogeneity, we prefer stratification or meta-analysis methods, but we encourage investigators to consider their specific study conditions and objectives. PMID:25647087
Giganti, Mark J; Luz, Paula M; Caro-Vega, Yanink; Cesar, Carina; Padgett, Denis; Koenig, Serena; Echevarria, Juan; McGowan, Catherine C; Shepherd, Bryan E
2015-05-01
Many studies of HIV/AIDS aggregate data from multiple cohorts to improve power and generalizability. There are several analysis approaches to account for cross-cohort heterogeneity; we assessed how different approaches can impact results from an HIV/AIDS study investigating predictors of mortality. Using data from 13,658 HIV-infected patients starting antiretroviral therapy from seven Latin American and Caribbean cohorts, we illustrate the assumptions of seven readily implementable approaches to account for across cohort heterogeneity with Cox proportional hazards models, and we compare hazard ratio estimates across approaches. As a sensitivity analysis, we modify cohort membership to generate specific heterogeneity conditions. Hazard ratio estimates varied slightly between the seven analysis approaches, but differences were not clinically meaningful. Adjusted hazard ratio estimates for the association between AIDS at treatment initiation and death varied from 2.00 to 2.20 across approaches that accounted for heterogeneity; the adjusted hazard ratio was estimated as 1.73 in analyses that ignored across cohort heterogeneity. In sensitivity analyses with more extreme heterogeneity, we noted a slightly greater distinction between approaches. Despite substantial heterogeneity between cohorts, the impact of the specific approach to account for heterogeneity was minimal in our case study. Our results suggest that it is important to account for across cohort heterogeneity in analyses, but that the specific technique for addressing heterogeneity may be less important. Because of their flexibility in accounting for cohort heterogeneity, we prefer stratification or meta-analysis methods, but we encourage investigators to consider their specific study conditions and objectives. PMID:25647087
Ong, Hong Choon; Alih, Ekele
2015-01-01
The tendency for experimental and industrial variables to include a certain proportion of outliers has become a rule rather than an exception. These clusters of outliers, if left undetected, have the capability to distort the mean and the covariance matrix of the Hotelling’s T2 multivariate control charts constructed to monitor individual quality characteristics. The effect of this distortion is that the control chart constructed from it becomes unreliable as it exhibits masking and swamping, a phenomenon in which an out-of-control process is erroneously declared as an in-control process or an in-control process is erroneously declared as out-of-control process. To handle these problems, this article proposes a control chart that is based on cluster-regression adjustment for retrospective monitoring of individual quality characteristics in a multivariate setting. The performance of the proposed method is investigated through Monte Carlo simulation experiments and historical datasets. Results obtained indicate that the proposed method is an improvement over the state-of-art methods in terms of outlier detection as well as keeping masking and swamping rate under control. PMID:25923739
Barks, C.S.
1995-01-01
Storm-runoff water-quality data were used to verify and, when appropriate, adjust regional regression models previously developed to estimate urban storm- runoff loads and mean concentrations in Little Rock, Arkansas. Data collected at 5 representative sites during 22 storms from June 1992 through January 1994 compose the Little Rock data base. Comparison of observed values (0) of storm-runoff loads and mean concentrations to the predicted values (Pu) from the regional regression models for nine constituents (chemical oxygen demand, suspended solids, total nitrogen, total ammonia plus organic nitrogen as nitrogen, total phosphorus, dissolved phosphorus, total recoverable copper, total recoverable lead, and total recoverable zinc) shows large prediction errors ranging from 63 to several thousand percent. Prediction errors for six of the regional regression models are less than 100 percent, and can be considered reasonable for water-quality models. Differences between 0 and Pu are due to variability in the Little Rock data base and error in the regional models. Where applicable, a model adjustment procedure (termed MAP-R-P) based upon regression with 0 against Pu was applied to improve predictive accuracy. For 11 of the 18 regional water-quality models, 0 and Pu are significantly correlated, that is much of the variation in 0 is explained by the regional models. Five of these 11 regional models consistently overestimate O; therefore, MAP-R-P can be used to provide a better estimate. For the remaining seven regional models, 0 and Pu are not significanfly correlated, thus neither the unadjusted regional models nor the MAP-R-P is appropriate. A simple estimator, such as the mean of the observed values may be used if the regression models are not appropriate. Standard error of estimate of the adjusted models ranges from 48 to 130 percent. Calibration results may be biased due to the limited data set sizes in the Little Rock data base. The relatively large values of
Quantile Regression Adjusting for Dependent Censoring from Semi-Competing Risks
Li, Ruosha; Peng, Limin
2014-01-01
Summary In this work, we study quantile regression when the response is an event time subject to potentially dependent censoring. We consider the semi-competing risks setting, where time to censoring remains observable after the occurrence of the event of interest. While such a scenario frequently arises in biomedical studies, most of current quantile regression methods for censored data are not applicable because they generally require the censoring time and the event time be independent. By imposing rather mild assumptions on the association structure between the time-to-event response and the censoring time variable, we propose quantile regression procedures, which allow us to garner a comprehensive view of the covariate effects on the event time outcome as well as to examine the informativeness of censoring. An efficient and stable algorithm is provided for implementing the new method. We establish the asymptotic properties of the resulting estimators including uniform consistency and weak convergence. The theoretical development may serve as a useful template for addressing estimating settings that involve stochastic integrals. Extensive simulation studies suggest that the proposed method performs well with moderate sample sizes. We illustrate the practical utility of our proposals through an application to a bone marrow transplant trial. PMID:25574152
Hoos, Anne B.; Patel, Anant R.
1996-01-01
Model-adjustment procedures were applied to the combined data bases of storm-runoff quality for Chattanooga, Knoxville, and Nashville, Tennessee, to improve predictive accuracy for storm-runoff quality for urban watersheds in these three cities and throughout Middle and East Tennessee. Data for 45 storms at 15 different sites (five sites in each city) constitute the data base. Comparison of observed values of storm-runoff load and event-mean concentration to the predicted values from the regional regression models for 10 constituents shows prediction errors, as large as 806,000 percent. Model-adjustment procedures, which combine the regional model predictions with local data, are applied to improve predictive accuracy. Standard error of estimate after model adjustment ranges from 67 to 322 percent. Calibration results may be biased due to sampling error in the Tennessee data base. The relatively large values of standard error of estimate for some of the constituent models, although representing significant reduction (at least 50 percent) in prediction error compared to estimation with unadjusted regional models, may be unacceptable for some applications. The user may wish to collect additional local data for these constituents and repeat the analysis, or calibrate an independent local regression model.
Li, Li; Brumback, Babette A; Weppelmann, Thomas A; Morris, J Glenn; Ali, Afsar
2016-08-15
Motivated by an investigation of the effect of surface water temperature on the presence of Vibrio cholerae in water samples collected from different fixed surface water monitoring sites in Haiti in different months, we investigated methods to adjust for unmeasured confounding due to either of the two crossed factors site and month. In the process, we extended previous methods that adjust for unmeasured confounding due to one nesting factor (such as site, which nests the water samples from different months) to the case of two crossed factors. First, we developed a conditional pseudolikelihood estimator that eliminates fixed effects for the levels of each of the crossed factors from the estimating equation. Using the theory of U-Statistics for independent but non-identically distributed vectors, we show that our estimator is consistent and asymptotically normal, but that its variance depends on the nuisance parameters and thus cannot be easily estimated. Consequently, we apply our estimator in conjunction with a permutation test, and we investigate use of the pigeonhole bootstrap and the jackknife for constructing confidence intervals. We also incorporate our estimator into a diagnostic test for a logistic mixed model with crossed random effects and no unmeasured confounding. For comparison, we investigate between-within models extended to two crossed factors. These generalized linear mixed models include covariate means for each level of each factor in order to adjust for the unmeasured confounding. We conduct simulation studies, and we apply the methods to the Haitian data. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26892025
Methods for Adjusting U.S. Geological Survey Rural Regression Peak Discharges in an Urban Setting
Moglen, Glenn E.; Shivers, Dorianne E.
2006-01-01
A study was conducted of 78 U.S. Geological Survey gaged streams that have been subjected to varying degrees of urbanization over the last three decades. Flood-frequency analysis coupled with nonlinear regression techniques were used to generate a set of equations for converting peak discharge estimates determined from rural regression equations to a set of peak discharge estimates that represent known urbanization. Specifically, urban regression equations for the 2-, 5-, 10-, 25-, 50-, 100-, and 500-year return periods were calibrated as a function of the corresponding rural peak discharge and the percentage of impervious area in a watershed. The results of this study indicate that two sets of equations, one set based on imperviousness and one set based on population density, performed well. Both sets of equations are dependent on rural peak discharges, a measure of development (average percentage of imperviousness or average population density), and a measure of homogeneity of development within a watershed. Average imperviousness was readily determined by using geographic information system methods and commonly available land-cover data. Similarly, average population density was easily determined from census data. Thus, a key advantage to the equations developed in this study is that they do not require field measurements of watershed characteristics as did the U.S. Geological Survey urban equations developed in an earlier investigation. During this study, the U.S. Geological Survey PeakFQ program was used as an integral tool in the calibration of all equations. The scarcity of historical land-use data, however, made exclusive use of flow records necessary for the 30-year period from 1970 to 2000. Such relatively short-duration streamflow time series required a nonstandard treatment of the historical data function of the PeakFQ program in comparison to published guidelines. Thus, the approach used during this investigation does not fully comply with the
Ho Hoang, Khai-Long; Mombaur, Katja
2015-10-15
Dynamic modeling of the human body is an important tool to investigate the fundamentals of the biomechanics of human movement. To model the human body in terms of a multi-body system, it is necessary to know the anthropometric parameters of the body segments. For young healthy subjects, several data sets exist that are widely used in the research community, e.g. the tables provided by de Leva. None such comprehensive anthropometric parameter sets exist for elderly people. It is, however, well known that body proportions change significantly during aging, e.g. due to degenerative effects in the spine, such that parameters for young people cannot be used for realistically simulating the dynamics of elderly people. In this study, regression equations are derived from the inertial parameters, center of mass positions, and body segment lengths provided by de Leva to be adjustable to the changes in proportion of the body parts of male and female humans due to aging. Additional adjustments are made to the reference points of the parameters for the upper body segments as they are chosen in a more practicable way in the context of creating a multi-body model in a chain structure with the pelvis representing the most proximal segment. PMID:26338096
Jen, Min-Hua; Bottle, Alex; Kirkwood, Graham; Johnston, Ron; Aylin, Paul
2011-09-01
We have previously described a system for monitoring a number of healthcare outcomes using case-mix adjustment models. It is desirable to automate the model fitting process in such a system if monitoring covers a large number of outcome measures or subgroup analyses. Our aim was to compare the performance of three different variable selection strategies: "manual", "automated" backward elimination and re-categorisation, and including all variables at once, irrespective of their apparent importance, with automated re-categorisation. Logistic regression models for predicting in-hospital mortality and emergency readmission within 28 days were fitted to an administrative database for 78 diagnosis groups and 126 procedures from 1996 to 2006 for National Health Services hospital trusts in England. The performance of models was assessed with Receiver Operating Characteristic (ROC) c statistics, (measuring discrimination) and Brier score (assessing the average of the predictive accuracy). Overall, discrimination was similar for diagnoses and procedures and consistently better for mortality than for emergency readmission. Brier scores were generally low overall (showing higher accuracy) and were lower for procedures than diagnoses, with a few exceptions for emergency readmission within 28 days. Among the three variable selection strategies, the automated procedure had similar performance to the manual method in almost all cases except low-risk groups with few outcome events. For the rapid generation of multiple case-mix models we suggest applying automated modelling to reduce the time required, in particular when examining different outcomes of large numbers of procedures and diseases in routinely collected administrative health data. PMID:21556848
Sneeringer, Stacy
2010-04-01
While a recent paper by Cox in this journal uses as its motivating factor the benefits of quantitative risk assessment, its content is entirely devoted to critiquing Sneeringer's article in the American Journal of Agricultural Economics. Cox's two main critiques of Sneeringer are fundamentally flawed and misrepresent the original article. Cox posits that Sneeringer did A and B, and then argues why A and B are incorrect. However, Sneeringer in fact did C and D; thus critiques of A and B are not applicable to Sneeringer's analysis. PMID:20345577
Covariate analysis of survival data: a small-sample study of Cox's model
Johnson, M.E.; Tolley, H.D.; Bryson, M.C.; Goldman, A.S.
1982-09-01
Cox's proportional-hazards model is frequently used to adjust for covariate effects in survival-data analysis. The small-sample performances of the maximum partial likelihood estimators of the regression parameters in a two-covariate hazard function model are evaluated with respect to bias, variance, and power in hypothesis tests. Previous Monte Carlo work on the two-sample problem is reviewed.
ERIC Educational Resources Information Center
Tipton, Elizabeth; Pustejovsky, James E.
2015-01-01
Randomized experiments are commonly used to evaluate the effectiveness of educational interventions. The goal of the present investigation is to develop small-sample corrections for multiple contrast hypothesis tests (i.e., F-tests) such as the omnibus test of meta-regression fit or a test for equality of three or more levels of a categorical…
ERIC Educational Resources Information Center
Thatcher, Greg W.; Henson, Robin K.
This study examined research in training and development to determine effect size reporting practices. It focused on the reporting of corrected effect sizes in research articles using multiple regression analyses. When possible, researchers calculated corrected effect sizes and determine if the associated shrinkage could have impacted researcher…
Gene-Based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions.
Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y; Chen, Wei
2016-02-01
Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, here we develop Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT), which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. PMID:26782979
Observational Studies: Matching or Regression?
Brazauskas, Ruta; Logan, Brent R
2016-03-01
In observational studies with an aim of assessing treatment effect or comparing groups of patients, several approaches could be used. Often, baseline characteristics of patients may be imbalanced between groups, and adjustments are needed to account for this. It can be accomplished either via appropriate regression modeling or, alternatively, by conducting a matched pairs study. The latter is often chosen because it makes groups appear to be comparable. In this article we considered these 2 options in terms of their ability to detect a treatment effect in time-to-event studies. Our investigation shows that a Cox regression model applied to the entire cohort is often a more powerful tool in detecting treatment effect as compared with a matched study. Real data from a hematopoietic cell transplantation study is used as an example. PMID:26712591
Kjelstrom, L.C.
1995-01-01
Previously developed U.S. Geological Survey regional regression models of runoff and 11 chemical constituents were evaluated to assess their suitability for use in urban areas in Boise and Garden City. Data collected in the study area were used to develop adjusted regional models of storm-runoff volumes and mean concentrations and loads of chemical oxygen demand, dissolved and suspended solids, total nitrogen and total ammonia plus organic nitrogen as nitrogen, total and dissolved phosphorus, and total recoverable cadmium, copper, lead, and zinc. Explanatory variables used in these models were drainage area, impervious area, land-use information, and precipitation data. Mean annual runoff volume and loads at the five outfalls were estimated from 904 individual storms during 1976 through 1993. Two methods were used to compute individual storm loads. The first method used adjusted regional models of storm loads and the second used adjusted regional models for mean concentration and runoff volume. For large storms, the first method seemed to produce excessively high loads for some constituents and the second method provided more reliable results for all constituents except suspended solids. The first method provided more reliable results for large storms for suspended solids.
Asquith, William H.; Roussel, Meghan C.
2009-01-01
Annual peak-streamflow frequency estimates are needed for flood-plain management; for objective assessment of flood risk; for cost-effective design of dams, levees, and other flood-control structures; and for design of roads, bridges, and culverts. Annual peak-streamflow frequency represents the peak streamflow for nine recurrence intervals of 2, 5, 10, 25, 50, 100, 200, 250, and 500 years. Common methods for estimation of peak-streamflow frequency for ungaged or unmonitored watersheds are regression equations for each recurrence interval developed for one or more regions; such regional equations are the subject of this report. The method is based on analysis of annual peak-streamflow data from U.S. Geological Survey streamflow-gaging stations (stations). Beginning in 2007, the U.S. Geological Survey, in cooperation with the Texas Department of Transportation and in partnership with Texas Tech University, began a 3-year investigation concerning the development of regional equations to estimate annual peak-streamflow frequency for undeveloped watersheds in Texas. The investigation focuses primarily on 638 stations with 8 or more years of data from undeveloped watersheds and other criteria. The general approach is explicitly limited to the use of L-moment statistics, which are used in conjunction with a technique of multi-linear regression referred to as PRESS minimization. The approach used to develop the regional equations, which was refined during the investigation, is referred to as the 'L-moment-based, PRESS-minimized, residual-adjusted approach'. For the approach, seven unique distributions are fit to the sample L-moments of the data for each of 638 stations and trimmed means of the seven results of the distributions for each recurrence interval are used to define the station specific, peak-streamflow frequency. As a first iteration of regression, nine weighted-least-squares, PRESS-minimized, multi-linear regression equations are computed using the watershed
Robertson, D.M.; Saad, D.A.; Heisey, D.M.
2006-01-01
Various approaches are used to subdivide large areas into regions containing streams that have similar reference or background water quality and that respond similarly to different factors. For many applications, such as establishing reference conditions, it is preferable to use physical characteristics that are not affected by human activities to delineate these regions. However, most approaches, such as ecoregion classifications, rely on land use to delineate regions or have difficulties compensating for the effects of land use. Land use not only directly affects water quality, but it is often correlated with the factors used to define the regions. In this article, we describe modifications to SPARTA (spatial regression-tree analysis), a relatively new approach applied to water-quality and environmental characteristic data to delineate zones with similar factors affecting water quality. In this modified approach, land-use-adjusted (residualized) water quality and environmental characteristics are computed for each site. Regression-tree analysis is applied to the residualized data to determine the most statistically important environmental characteristics describing the distribution of a specific water-quality constituent. Geographic information for small basins throughout the study area is then used to subdivide the area into relatively homogeneous environmental water-quality zones. For each zone, commonly used approaches are subsequently used to define its reference water quality and how its water quality responds to changes in land use. SPARTA is used to delineate zones of similar reference concentrations of total phosphorus and suspended sediment throughout the upper Midwestern part of the United States. ?? 2006 Springer Science+Business Media, Inc.
Technology Transfer Automated Retrieval System (TEKTRAN)
A method of accounting for differences in variation in components of test-day milk production records was developed. This method could improve the accuracy of genetic evaluations. A random regression model is used to analyze the data, then a transformation is applied to the random regression coeffic...
ERIC Educational Resources Information Center
Johns, Stephanie
2010-01-01
Kathy Cox, the superintendent of schools for Georgia, believes "excellence is not an accident". She made a name for herself by winning $1 million proving she was smarter than a fifth-grader on a popular television show. This article presents a profile of Cox, her family, her role as school superintendent, and her accomplishments. Although she…
Quality Reporting of Multivariable Regression Models in Observational Studies
Real, Jordi; Forné, Carles; Roso-Llorach, Albert; Martínez-Sánchez, Jose M.
2016-01-01
Abstract Controlling for confounders is a crucial step in analytical observational studies, and multivariable models are widely used as statistical adjustment techniques. However, the validation of the assumptions of the multivariable regression models (MRMs) should be made clear in scientific reporting. The objective of this study is to review the quality of statistical reporting of the most commonly used MRMs (logistic, linear, and Cox regression) that were applied in analytical observational studies published between 2003 and 2014 by journals indexed in MEDLINE. Review of a representative sample of articles indexed in MEDLINE (n = 428) with observational design and use of MRMs (logistic, linear, and Cox regression). We assessed the quality of reporting about: model assumptions and goodness-of-fit, interactions, sensitivity analysis, crude and adjusted effect estimate, and specification of more than 1 adjusted model. The tests of underlying assumptions or goodness-of-fit of the MRMs used were described in 26.2% (95% CI: 22.0–30.3) of the articles and 18.5% (95% CI: 14.8–22.1) reported the interaction analysis. Reporting of all items assessed was higher in articles published in journals with a higher impact factor. A low percentage of articles indexed in MEDLINE that used multivariable techniques provided information demonstrating rigorous application of the model selected as an adjustment method. Given the importance of these methods to the final results and conclusions of observational studies, greater rigor is required in reporting the use of MRMs in the scientific literature. PMID:27196467
NASA Astrophysics Data System (ADS)
Liberman, Neomi; Ben-David Kolikant, Yifat; Beeri, Catriel
2012-09-01
Due to a program reform in Israel, experienced CS high-school teachers faced the need to master and teach a new programming paradigm. This situation served as an opportunity to explore the relationship between teachers' content knowledge (CK) and their pedagogical content knowledge (PCK). This article focuses on three case studies, with emphasis on one of them. Using observations and interviews, we examine how the teachers, we observed taught and what development of their teaching occurred as a result of their teaching experience, if at all. Our findings suggest that this situation creates a new hybrid state of teachers, which we term "regressed experts." These teachers incorporate in their professional practice some elements typical of novices and some typical of experts. We also found that these teachers' experience, although established when teaching a different CK, serve as a leverage to improve their knowledge and understanding of aspects of the new content.
Quantile Regression with Censored Data
ERIC Educational Resources Information Center
Lin, Guixian
2009-01-01
The Cox proportional hazards model and the accelerated failure time model are frequently used in survival data analysis. They are powerful, yet have limitation due to their model assumptions. Quantile regression offers a semiparametric approach to model data with possible heterogeneity. It is particularly powerful for censored responses, where the…
Parra, Edwin Roger; Lin, Flavia; Martins, Vanessa; Rangel, Maristela Peres; Capelozzi, Vera Luiza
2013-01-01
OBJECTIVE: To study the expression of COX-1 and COX-2 in the remodeled lung in systemic sclerosis (SSc) and idiopathic pulmonary fibrosis (IPF) patients, correlating that expression with patient survival. METHODS: We examined open lung biopsy specimens from 24 SSc patients and 30 IPF patients, using normal lung tissue as a control. The histological patterns included fibrotic nonspecific interstitial pneumonia (NSIP) in SSc patients and usual interstitial pneumonia (UIP) in IPF patients. We used immunohistochemistry and histomorphometry to evaluate the expression of COX-1 and COX-2 in alveolar septa, vessels, and bronchioles. We then correlated that expression with pulmonary function test results and evaluated its impact on patient survival. RESULTS: The expression of COX-1 and COX-2 in alveolar septa was significantly higher in IPF-UIP and SSc-NSIP lung tissue than in the control tissue. No difference was found between IPF-UIP and SSc-NSIP tissue regarding COX-1 and COX-2 expression. Multivariate analysis based on the Cox regression model showed that the factors associated with a low risk of death were younger age, high DLCO/alveolar volume, IPF, and high COX-1 expression in alveolar septa, whereas those associated with a high risk of death were advanced age, low DLCO/alveolar volume, SSc (with NSIP), and low COX-1 expression in alveolar septa. CONCLUSIONS: Our findings suggest that strategies aimed at preventing low COX-1 synthesis will have a greater impact on SSc, whereas those aimed at preventing high COX-2 synthesis will have a greater impact on IPF. However, prospective randomized clinical trials are needed in order to confirm that. PMID:24473763
Regression calibration method for correcting measurement-error bias in nutritional epidemiology.
Spiegelman, D; McDermott, A; Rosner, B
1997-04-01
Regression calibration is a statistical method for adjusting point and interval estimates of effect obtained from regression models commonly used in epidemiology for bias due to measurement error in assessing nutrients or other variables. Previous work developed regression calibration for use in estimating odds ratios from logistic regression. We extend this here to estimating incidence rate ratios from Cox proportional hazards models and regression slopes from linear-regression models. Regression calibration is appropriate when a gold standard is available in a validation study and a linear measurement error with constant variance applies or when replicate measurements are available in a reliability study and linear random within-person error can be assumed. In this paper, the method is illustrated by correction of rate ratios describing the relations between the incidence of breast cancer and dietary intakes of vitamin A, alcohol, and total energy in the Nurses' Health Study. An example using linear regression is based on estimation of the relation between ultradistal radius bone density and dietary intakes of caffeine, calcium, and total energy in the Massachusetts Women's Health Study. Software implementing these methods uses SAS macros. PMID:9094918
Prognostic models in coronary artery disease: Cox and network approaches
Mora, Antonio; Sicari, Rosa; Cortigiani, Lauro; Carpeggiani, Clara; Picano, Eugenio; Capobianco, Enrico
2015-01-01
Predictive assessment of the risk of developing cardiovascular diseases is usually provided by computational approaches centred on Cox models. The complex interdependence structure underlying clinical data patterns can limit the performance of Cox analysis and complicate the interpretation of results, thus calling for complementary and integrative methods. Prognostic models are proposed for studying the risk associated with patients with known or suspected coronary artery disease (CAD) undergoing vasodilator stress echocardiography, an established technique for CAD detection and prognostication. In order to complement standard Cox models, network inference is considered a possible solution to quantify the complex relationships between heterogeneous data categories. In particular, a mutual information network is designed to explore the paths linking patient-associated variables to endpoint events, to reveal prognostic factors and to identify the best possible predictors of death. Data from a prospective, multicentre, observational study are available from a previous study, based on 4313 patients (2532 men; 64±11 years) with known (n=1547) or suspected (n=2766) CAD, who underwent high-dose dipyridamole (0.84 mg kg−1 over 6 min) stress echocardiography with coronary flow reserve (CFR) evaluation of left anterior descending (LAD) artery by Doppler. The overall mortality was the only endpoint analysed by Cox models. The estimated connectivity between clinical variables assigns a complementary value to the proposed network approach in relation to the established Cox model, for instance revealing connectivity paths. Depending on the use of multiple metrics, the constraints of regression analysis in measuring the association strength among clinical variables can be relaxed, and identification of communities and prognostic paths can be provided. On the basis of evidence from various model comparisons, we show in this CAD study that there may be characteristic
Prognostic models in coronary artery disease: Cox and network approaches.
Mora, Antonio; Sicari, Rosa; Cortigiani, Lauro; Carpeggiani, Clara; Picano, Eugenio; Capobianco, Enrico
2015-02-01
Predictive assessment of the risk of developing cardiovascular diseases is usually provided by computational approaches centred on Cox models. The complex interdependence structure underlying clinical data patterns can limit the performance of Cox analysis and complicate the interpretation of results, thus calling for complementary and integrative methods. Prognostic models are proposed for studying the risk associated with patients with known or suspected coronary artery disease (CAD) undergoing vasodilator stress echocardiography, an established technique for CAD detection and prognostication. In order to complement standard Cox models, network inference is considered a possible solution to quantify the complex relationships between heterogeneous data categories. In particular, a mutual information network is designed to explore the paths linking patient-associated variables to endpoint events, to reveal prognostic factors and to identify the best possible predictors of death. Data from a prospective, multicentre, observational study are available from a previous study, based on 4313 patients (2532 men; 64±11 years) with known (n=1547) or suspected (n=2766) CAD, who underwent high-dose dipyridamole (0.84 mg kg(-1) over 6 min) stress echocardiography with coronary flow reserve (CFR) evaluation of left anterior descending (LAD) artery by Doppler. The overall mortality was the only endpoint analysed by Cox models. The estimated connectivity between clinical variables assigns a complementary value to the proposed network approach in relation to the established Cox model, for instance revealing connectivity paths. Depending on the use of multiple metrics, the constraints of regression analysis in measuring the association strength among clinical variables can be relaxed, and identification of communities and prognostic paths can be provided. On the basis of evidence from various model comparisons, we show in this CAD study that there may be characteristic
NASA Astrophysics Data System (ADS)
Grégoire, G.
2014-12-01
The logistic regression originally is intended to explain the relationship between the probability of an event and a set of covariables. The model's coefficients can be interpreted via the odds and odds ratio, which are presented in introduction of the chapter. The observations are possibly got individually, then we speak of binary logistic regression. When they are grouped, the logistic regression is said binomial. In our presentation we mainly focus on the binary case. For statistical inference the main tool is the maximum likelihood methodology: we present the Wald, Rao and likelihoods ratio results and their use to compare nested models. The problems we intend to deal with are essentially the same as in multiple linear regression: testing global effect, individual effect, selection of variables to build a model, measure of the fitness of the model, prediction of new values… . The methods are demonstrated on data sets using R. Finally we briefly consider the binomial case and the situation where we are interested in several events, that is the polytomous (multinomial) logistic regression and the particular case of ordinal logistic regression.
External validation of a Cox prognostic model: principles and methods
2013-01-01
Background A prognostic model should not enter clinical practice unless it has been demonstrated that it performs a useful role. External validation denotes evaluation of model performance in a sample independent of that used to develop the model. Unlike for logistic regression models, external validation of Cox models is sparsely treated in the literature. Successful validation of a model means achieving satisfactory discrimination and calibration (prediction accuracy) in the validation sample. Validating Cox models is not straightforward because event probabilities are estimated relative to an unspecified baseline function. Methods We describe statistical approaches to external validation of a published Cox model according to the level of published information, specifically (1) the prognostic index only, (2) the prognostic index together with Kaplan-Meier curves for risk groups, and (3) the first two plus the baseline survival curve (the estimated survival function at the mean prognostic index across the sample). The most challenging task, requiring level 3 information, is assessing calibration, for which we suggest a method of approximating the baseline survival function. Results We apply the methods to two comparable datasets in primary breast cancer, treating one as derivation and the other as validation sample. Results are presented for discrimination and calibration. We demonstrate plots of survival probabilities that can assist model evaluation. Conclusions Our validation methods are applicable to a wide range of prognostic studies and provide researchers with a toolkit for external validation of a published Cox model. PMID:23496923
NASA Astrophysics Data System (ADS)
Coe, Rob; Dalrymple, Brent
More than 1000 friends, students, and colleagues from all over the country filled Stanford Memorial Chapel (Stanford, Calif.) on February 3, 1987, to join in “A Celebration of the Life of Allan Cox.” Allan died early on the morning of January 27 while bicycling, the sport he had come to love the most. Between pieces of his favorite music by Bach and Mozart, Stanford administrators and colleagues spoke in tribute of Allan's unique qualities as friend, scientist, teacher, and dean of the School of Earth Sciences. James Rosse, Vice President and Provost of Stanford University, struck a particularly resonant chord with his personal remarks: "Allan reached out to each person he knew with the warmth and attention that can only come from deep respect and affection for others. I never heard him speak ill of others, and I do not believe he was capable of doing anything that would harm another being. He cared too much to intrude where he was not wanted, but his curiosity about people and the loving care with which he approached them broke down reserve to create remarkable friendships. His enthusiasm and good humor made him a welcome guest in the hearts of the hundreds of students and colleagues who shared the opportunity of knowing Allan Cox as a person."
Biochemistry of cyclooxygenase (COX)-2 inhibitors and molecular pathology of COX-2 in neoplasia.
Fosslien, E
2000-10-01
Several types of human tumors overexpress cyclooxygenase (COX) -2 but not COX-1, and gene knockout transfection experiments demonstrate a central role of COX-2 in experimental tumorigenesis. COX-2 produces prostaglandins that inhibit apoptosis and stimulate angiogenesis and invasiveness. Selective COX-2 inhibitors reduce prostaglandin synthesis, restore apoptosis, and inhibit cancer cell proliferation. In animal studies they limit carcinogen-induced tumorigenesis. In contrast, aspirin-like nonselective NSAIDs such as sulindac and indomethacin inhibit not only the enzymatic action of the highly inducible, proinflammatory COX-2 but the constitutively expressed, cytoprotective COX-1 as well. Consequently, nonselective NSAIDs can cause platelet dysfunction, gastrointestinal ulceration, and kidney damage. For that reason, selective inhibition of COX-2 to treat neoplastic proliferation is preferable to nonselective inhibition. Selective COX-2 inhibitors, such as meloxicam, celecoxib (SC-58635), and rofecoxib (MK-0966), are NSAIDs that have been modified chemically to preferentially inhibit COX-2 but not COX-1. For instance, meloxicam inhibits the growth of cultured colon cancer cells (HCA-7 and Moser-S) that express COX-2 but has no effect on HCT-116 tumor cells that do not express COX-2. NS-398 induces apoptosis in COX-2 expressing LNCaP prostate cancer cells and, surprisingly, in colon cancer S/KS cells that does not express COX-2. This effect may due to induction of apoptosis through uncoupling of oxidative phosphorylation and down-regulation of Bcl-2, as has been demonstrated for some nonselective NSAIDs, for instance, flurbiprofen. COX-2 mRNA and COX-2 protein is constitutively expressed in the kidney, brain, spinal cord, and ductus deferens, and in the uterus during implantation. In addition, COX-2 is constitutively and dominantly expressed in the pancreatic islet cells. These findings might somewhat limit the use of presently available selective COX-2 inhibitors
Huang, Dong; Cabral, Ricardo; De la Torre, Fernando
2016-02-01
Discriminative methods (e.g., kernel regression, SVM) have been extensively used to solve problems such as object recognition, image alignment and pose estimation from images. These methods typically map image features ( X) to continuous (e.g., pose) or discrete (e.g., object category) values. A major drawback of existing discriminative methods is that samples are directly projected onto a subspace and hence fail to account for outliers common in realistic training sets due to occlusion, specular reflections or noise. It is important to notice that existing discriminative approaches assume the input variables X to be noise free. Thus, discriminative methods experience significant performance degradation when gross outliers are present. Despite its obvious importance, the problem of robust discriminative learning has been relatively unexplored in computer vision. This paper develops the theory of robust regression (RR) and presents an effective convex approach that uses recent advances on rank minimization. The framework applies to a variety of problems in computer vision including robust linear discriminant analysis, regression with missing data, and multi-label classification. Several synthetic and real examples with applications to head pose estimation from images, image and video classification and facial attribute classification with missing data are used to illustrate the benefits of RR. PMID:26761740
Cologne, John; Hsu, Wan-Ling; Abbott, Robert D; Ohishi, Waka; Grant, Eric J; Fujiwara, Saeko; Cullings, Harry M
2012-07-01
In epidemiologic cohort studies of chronic diseases, such as heart disease or cancer, confounding by age can bias the estimated effects of risk factors under study. With Cox proportional-hazards regression modeling in such studies, it would generally be recommended that chronological age be handled nonparametrically as the primary time scale. However, studies involving baseline measurements of biomarkers or other factors frequently use follow-up time since measurement as the primary time scale, with no explicit justification. The effects of age are adjusted for by modeling age at entry as a parametric covariate. Parametric adjustment raises the question of model adequacy, in that it assumes a known functional relationship between age and disease, whereas using age as the primary time scale does not. We illustrate this graphically and show intuitively why the parametric approach to age adjustment using follow-up time as the primary time scale provides a poor approximation to age-specific incidence. Adequate parametric adjustment for age could require extensive modeling, which is wasteful, given the simplicity of using age as the primary time scale. Furthermore, the underlying hazard with follow-up time based on arbitrary timing of study initiation may have no inherent meaning in terms of risk. Given the potential for biased risk estimates, age should be considered as the preferred time scale for proportional-hazards regression with epidemiologic follow-up data when confounding by age is a concern. PMID:22517300
COX7AR is a Stress-inducible Mitochondrial COX Subunit that Promotes Breast Cancer Malignancy.
Zhang, Kezhong; Wang, Guohui; Zhang, Xuebao; Hüttemann, Philipp P; Qiu, Yining; Liu, Jenney; Mitchell, Allison; Lee, Icksoo; Zhang, Chao; Lee, Jin-Sook; Pecina, Petr; Wu, Guojun; Yang, Zeng-Quan; Hüttemann, Maik; Grossman, Lawrence I
2016-01-01
Cytochrome c oxidase (COX), the terminal enzyme of the mitochondrial respiratory chain, plays a key role in regulating mitochondrial energy production and cell survival. COX subunit VIIa polypeptide 2-like protein (COX7AR) is a novel COX subunit that was recently found to be involved in mitochondrial supercomplex assembly and mitochondrial respiration activity. Here, we report that COX7AR is expressed in high energy-demanding tissues, such as brain, heart, liver, and aggressive forms of human breast cancer cells. Under cellular stress that stimulates energy metabolism, COX7AR is induced and incorporated into the mitochondrial COX complex. Functionally, COX7AR promotes cellular energy production in human mammary epithelial cells. Gain- and loss-of-function analysis demonstrates that COX7AR is required for human breast cancer cells to maintain higher rates of proliferation, clone formation, and invasion. In summary, our study revealed that COX7AR is a stress-inducible mitochondrial COX subunit that facilitates human breast cancer malignancy. These findings have important implications in the understanding and treatment of human breast cancer and the diseases associated with mitochondrial energy metabolism. PMID:27550821
COX7AR is a Stress-inducible Mitochondrial COX Subunit that Promotes Breast Cancer Malignancy
Zhang, Kezhong; Wang, Guohui; Zhang, Xuebao; Hüttemann, Philipp P.; Qiu, Yining; Liu, Jenney; Mitchell, Allison; Lee, Icksoo; Zhang, Chao; Lee, Jin-sook; Pecina, Petr; Wu, Guojun; Yang, Zeng-quan; Hüttemann, Maik; Grossman, Lawrence I.
2016-01-01
Cytochrome c oxidase (COX), the terminal enzyme of the mitochondrial respiratory chain, plays a key role in regulating mitochondrial energy production and cell survival. COX subunit VIIa polypeptide 2-like protein (COX7AR) is a novel COX subunit that was recently found to be involved in mitochondrial supercomplex assembly and mitochondrial respiration activity. Here, we report that COX7AR is expressed in high energy-demanding tissues, such as brain, heart, liver, and aggressive forms of human breast cancer cells. Under cellular stress that stimulates energy metabolism, COX7AR is induced and incorporated into the mitochondrial COX complex. Functionally, COX7AR promotes cellular energy production in human mammary epithelial cells. Gain- and loss-of-function analysis demonstrates that COX7AR is required for human breast cancer cells to maintain higher rates of proliferation, clone formation, and invasion. In summary, our study revealed that COX7AR is a stress-inducible mitochondrial COX subunit that facilitates human breast cancer malignancy. These findings have important implications in the understanding and treatment of human breast cancer and the diseases associated with mitochondrial energy metabolism. PMID:27550821
Decomposition of Variance for Spatial Cox Processes
Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus
2012-01-01
Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with additive or log linear random intensity functions. We moreover consider a new and flexible class of pair correlation function models given in terms of normal variance mixture covariance functions. The proposed methodology is applied to point pattern data sets of locations of tropical rain forest trees. PMID:23599558
Real, Jordi; Forné, Carles; Roso-Llorach, Albert; Martínez-Sánchez, Jose M
2016-05-01
Controlling for confounders is a crucial step in analytical observational studies, and multivariable models are widely used as statistical adjustment techniques. However, the validation of the assumptions of the multivariable regression models (MRMs) should be made clear in scientific reporting. The objective of this study is to review the quality of statistical reporting of the most commonly used MRMs (logistic, linear, and Cox regression) that were applied in analytical observational studies published between 2003 and 2014 by journals indexed in MEDLINE.Review of a representative sample of articles indexed in MEDLINE (n = 428) with observational design and use of MRMs (logistic, linear, and Cox regression). We assessed the quality of reporting about: model assumptions and goodness-of-fit, interactions, sensitivity analysis, crude and adjusted effect estimate, and specification of more than 1 adjusted model.The tests of underlying assumptions or goodness-of-fit of the MRMs used were described in 26.2% (95% CI: 22.0-30.3) of the articles and 18.5% (95% CI: 14.8-22.1) reported the interaction analysis. Reporting of all items assessed was higher in articles published in journals with a higher impact factor.A low percentage of articles indexed in MEDLINE that used multivariable techniques provided information demonstrating rigorous application of the model selected as an adjustment method. Given the importance of these methods to the final results and conclusions of observational studies, greater rigor is required in reporting the use of MRMs in the scientific literature. PMID:27196467
Cyclooxygenase (COX) Inhibitors and the Newborn Kidney
Smith, Francine G.; Wade, Andrew W.; Lewis, Megan L.; Qi, Wei
2012-01-01
This review summarizes our current understanding of the role of cyclo-oxygenase inhibitors (COXI) in influencing the structural development as well as the function of the developing kidney. COXI administered either during pregnancy or after birth can influence kidney development including nephronogenesis, and can decrease renal perfusion and ultrafiltration potentially leading to acute kidney injury in the newborn period. To date, which COX isoform (COX-1 or COX-2) plays a more important role in during fetal development and influences kidney function early in life is not known, though evidence points to a predominant role for COX-2. Clinical implications of the use of COXI in pregnancy and in the newborn infant are also evaluated herein, with specific reference to the potential effects of COXI on nephronogenesis as well as newborn kidney function. PMID:24281306
COX-2 gene dosage-dependent defects in kidney development.
Slattery, Patrick; Frölich, Stefanie; Schreiber, Yannik; Nüsing, Rolf M
2016-05-15
Deletion of cyclooxygenase (COX)-2 causes impairment of kidney development, including hypothrophic glomeruli and cortical thinning. A critical role for COX-2 is seen 4-8 days postnatally. The present study was aimed at answering whether different COX-2 gene dosage and partial pharmacological COX-2 inhibition impairs kidney development. We studied kidney development in COX-2(+/+), COX-2(+/-), and COX-2(-/-) mice as well as in C57Bl6 mice treated postnatally with low (5 mg·kg(-1)·day(-1)) and high (10 mg·kg(-1)·day(-1)) doses of the selective COX-2 inhibitor SC-236. COX-2(+/-) mice exhibit impaired kidney development leading to reduced glomerular size but, in contrast to COX-2(-/-) mice, only marginal cortical thinning. Moreover, in COX-2(+/-) and COX-2(-/-) kidneys, juxtamedullary glomeruli, which develop in the very early stages of nephrogenesis, also showed a size reduction. In COX-2(+/-) kidneys at the age of 8 days, we observed significantly less expression of COX-2 mRNA and protein and less PGE2 and PGI2 synthetic activity compared with COX-2(+/+) kidneys. The renal defects in COX-2(-/-) and COX-2(+/-) kidneys could be mimicked by high and low doses of SC-236, respectively. In aged COX-2(+/-) kidneys, glomerulosclerosis was observed; however, in contrast to COX-2(-/-) kidneys, periglomerular fibrosis was absent. COX-2(+/-) mice showed signs of kidney insufficiency, demonstrated by enhanced serum creatinine levels, quite similar to COX-2(-/-) mice, but, in contrast, serum urea remained at the control level. In summary, function of both COX-2 gene alleles is absolutely necessary to ensure physiological development of the mouse kidney. Loss of one copy of the COX-2 gene or partial COX-2 inhibition is associated with distinct renal damage and reduced kidney function. PMID:26984955
Viscum album-Mediated COX-2 Inhibition Implicates Destabilization of COX-2 mRNA
Saha, Chaitrali; Hegde, Pushpa; Friboulet, Alain; Bayry, Jagadeesh; Kaveri, Srinivas V.
2015-01-01
Extensive use of Viscum album (VA) preparations in the complementary therapy of cancer and in several other human pathologies has led to an increasing number of cellular and molecular approaches to explore the mechanisms of action of VA. We have recently demonstrated that, VA preparations exert a potent anti-inflammatory effect by selectively down-regulating the COX-2-mediated cytokine-induced secretion of prostaglandin E2 (PGE2), one of the important molecular signatures of inflammatory reactions. In this study, we observed a significant down-regulation of COX-2 protein expression in VA-treated A549 cells however COX-2 mRNA levels were unaltered. Therefore, we hypothesized that VA induces destabilisation of COX-2 mRNA, thereby depleting the available functional COX-2 mRNA for the protein synthesis and for the subsequent secretion of PGE2. To address this question, we analyzed the molecular degradation of COX-2 protein and its corresponding mRNA in A549 cell line. Using cyclohexamide pulse chase experiment, we demonstrate that, COX-2 protein degradation is not affected by the treatment with VA whereas experiments on transcriptional blockade with actinomycin D, revealed a marked reduction in the half life of COX-2 mRNA due to its rapid degradation in the cells treated with VA compared to that in IL-1β-stimulated cells. These results thus demonstrate that VA-mediated inhibition of PGE2 implicates destabilization of COX-2 mRNA. PMID:25664986
Analysis of the correlation between P53 and Cox-2 expression and prognosis in esophageal cancer
CHEN, JUN; WU, FANG; PEI, HONG-LEI; GU, WEN-DONG; NING, ZHONG-HUA; SHAO, YING-JIE; HUANG, JIN
2015-01-01
The present study aimed to explore the importance of P53 and Cox-2 protein expression in esophageal cancer and assess their influence on prognosis. The expression of P53 and Cox-2 was assessed in esophageal cancer samples from 195 patients subjected to radical surgery at Changzhou First People's Hospital (Changzhou, China) between May 2010 and December 2011. Expression of P53 and Cox-2 proteins were detected in 60.5% (118/195) and 69.7% (136/195) of the samples, respectively, and were co-expressed in 43.1% (84/195) of the samples. A correlation was identified between P53 expression and overall survival (OS) (P=0.0351) as well as disease-free survival (DFS) (P=0.0307). In addition, the co-expression of P53 and Cox-2 also correlated with OS (P=0.0040) and DFS (P=0.0042). P53 expression (P=0.023), TNM staging (P<0.001) and P53/Cox-2 co-expression (P=0.009) were identified as independent factors affecting OS in patients with esophageal cancer via a Cox multivariate regression model analysis. A similar analysis also identified P53 expression (P=0.020), TNM staging (P<0.001) and P53/Cox-2 co-expression (P=0.008) as independent prognostic factors influencing DFS in these patients. Binary logistic regression analysis demonstrated a correlation between P53 expression (P=0.012), TNM staging (P<0.001), tumor differentiation level (P=0.023) and P53/Cox-2 co-expression (P=0.021), and local recurrence or distant esophageal cancer metastasis. The results of the present study indicate that P53 and Cox-2 proteins may act synergistically in the development of esophageal cancer, and the assessment of P53/Cox-2 co-expression status in esophageal cancer biopsies may become an important diagnostic criterion to evaluate the prognosis of patients with esophageal cancer. PMID:26622818
Select Dietary Phytochemicals Function as Inhibitors of COX-1 but Not COX-2
Li, Haitao; Zhu, Feng; Sun, Yanwen; Li, Bing; Oi, Naomi; Chen, Hanyong; Lubet, Ronald A.; Bode, Ann M.; Dong, Zigang
2013-01-01
Recent clinical trials raised concerns regarding the cardiovascular toxicity of selective cyclooxygenase-2 (COX-2) inhibitors. Many active dietary factors are reported to suppress carcinogenesis by targeting COX-2. A major question was accordingly raised: why has the lifelong use of phytochemicals that likely inhibit COX-2 presumably not been associated with adverse cardiovascular side effects. To answer this question, we selected a library of dietary-derived phytochemicals and evaluated their potential cardiovascular toxicity in human umbilical vein endothelial cells. Our data indicated that the possibility of cardiovascular toxicity of these dietary phytochemicals was low. Further mechanistic studies revealed that the actions of these phytochemicals were similar to aspirin in that they mainly inhibited COX-1 rather than COX-2, especially at low doses. PMID:24098505
ERIC Educational Resources Information Center
Pedrini, D. T.; Pedrini, Bonnie C.
Regression, another mechanism studied by Sigmund Freud, has had much research, e.g., hypnotic regression, frustration regression, schizophrenic regression, and infra-human-animal regression (often directly related to fixation). Many investigators worked with hypnotic age regression, which has a long history, going back to Russian reflexologists.…
Barrientos, Antoni; Gouget, Karine; Horn, Darryl; Soto, Ileana C.; Fontanesi, Flavia
2008-01-01
Eukaryotic cytochrome c oxidase (COX) is the terminal enzyme of the mitochondrial respiratory chain. COX is a multimeric enzyme formed by subunits of dual genetic origin whose assembly is intricate and highly regulated. In addition to the structural subunits, a large number of accessory factors are required to build the holoenzyme. The function of these factors is required in all stages of the assembly process. They are relevant to human health because devastating human disorders have been associated with mutations in nuclear genes encoding conserved COX assembly factors. The study of yeast strains and human cell lines from patients carrying mutations in structural subunits and COX assembly factors has been invaluable to attain the current state of knowledge, even if still fragmentary, of the COX assembly process. After the identification of the genes involved, the isolation and characterization of genetic and metabolic suppressors of COX assembly defects, reviewed here, have become a profitable strategy to gain insight into their functions and the pathways in which they operate. Additionally, they have the potential to provide useful information for devising therapeutic approaches to combat human disorders associated with COX deficiency. PMID:18522805
Oxidative switches in functioning of mammalian copper chaperone Cox17
Voronova, Anastassia; Meyer-Klaucke, Wolfram; Meyer, Thomas; Rompel, Annette; Krebs, Bernt; Kazantseva, Jekaterina; Sillard, Rannar; Palumaa, Peep
2007-01-01
Cox17, a copper chaperone for cytochrome-c oxidase, is an essential and highly conserved protein in eukaryotic organisms. Yeast and mammalian Cox17 share six conserved cysteine residues, which are involved in complex redox reactions as well as in metal binding and transfer. Mammalian Cox17 exists in three oxidative states, each characterized by distinct metal-binding properties: fully reduced mammalian Cox170S–S binds co-operatively to four Cu+; Cox172S–S, with two disulfide bridges, binds to one of either Cu+ or Zn2+; and Cox173S–S, with three disulfide bridges, does not bind to any metal ions. The Em (midpoint redox potential) values for two redox couples of Cox17, Cox173S–S↔Cox172S–S (Em1) and Cox172S–S↔Cox170S–S (Em2), were determined to be −197 mV and −340 mV respectively. The data indicate that an equilibrium exists in the cytosol between Cox170S-S and Cox172S–S, which is slightly shifted towards Cox170S-S. In the IMS (mitochondrial intermembrane space), the equilibrium is shifted towards Cox172S–S, enabling retention of Cox172S–S in the IMS and leading to the formation of a biologically competent form of the Cox17 protein, Cox172S–S, capable of copper transfer to the copper chaperone Sco1. XAS (X-ray absorption spectroscopy) determined that Cu4Cox17 contains a Cu4S6-type copper–thiolate cluster, which may provide safe storage of an excess of copper ions. PMID:17672825
Anandamide and decidual remodelling: COX-2 oxidative metabolism as a key regulator.
Almada, M; Piscitelli, F; Fonseca, B M; Di Marzo, V; Correia-da-Silva, G; Teixeira, N
2015-11-01
Recently, endocannabinoids have emerged as signalling mediators in reproduction. It is widely accepted that anandamide (AEA) levels must be tightly regulated, and that a disturbance in AEA levels may impact decidual stability and regression. We have previously characterized the endocannabinoid machinery in rat decidual tissue and reported the pro-apoptotic action of AEA on rat decidual cells. Cyclooxygenase-2 (COX-2) is an inducible enzyme that plays a crucial role in early pregnancy, and is also a key modulator in the crosstalk between endocannabinoids and prostaglandins. On the other hand, AEA-oxidative metabolism by COX-2 is not merely a mean to inactivate its action, but it yields the formation of a new class of mediators, named prostaglandin-ethanolamides, or prostamides. In this study we found that AEA-induced apoptosis in decidual cells involves COX-2 metabolic pathway. AEA induced COX-2 expression through p38 MAPK, resulting in the formation of prostamide E2 (PME2). Our findings also suggest that AEA-induced effect is associated with NF-kB activation. Finally, we describe the involvement of PME2 in the induction of the intrinsic apoptotic pathway in rat decidual cells. Altogether, our findings highlight the role of COX-2 as a gatekeeper in the uterine environment and clarify the impact of the deregulation of AEA levels on the decidual remodelling process. PMID:26335727
ELASTIC NET FOR COX'S PROPORTIONAL HAZARDS MODEL WITH A SOLUTION PATH ALGORITHM.
Wu, Yichao
2012-01-01
For least squares regression, Efron et al. (2004) proposed an efficient solution path algorithm, the least angle regression (LAR). They showed that a slight modification of the LAR leads to the whole LASSO solution path. Both the LAR and LASSO solution paths are piecewise linear. Recently Wu (2011) extended the LAR to generalized linear models and the quasi-likelihood method. In this work we extend the LAR further to handle Cox's proportional hazards model. The goal is to develop a solution path algorithm for the elastic net penalty (Zou and Hastie (2005)) in Cox's proportional hazards model. This goal is achieved in two steps. First we extend the LAR to optimizing the log partial likelihood plus a fixed small ridge term. Then we define a path modification, which leads to the solution path of the elastic net regularized log partial likelihood. Our solution path is exact and piecewise determined by ordinary differential equation systems. PMID:23226932
American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 5th ed. Arlington, Va: American Psychiatric Publishing. 2013. Powell AD. Grief, bereavement, and adjustment disorders. In: Stern TA, Rosenbaum ...
Golgi-Cox Staining Step by Step
Zaqout, Sami; Kaindl, Angela M.
2016-01-01
Golgi staining remains a key method to study neuronal morphology in vivo. Since most protocols delineating modifications of the original staining method lack details on critical steps, establishing this method in a laboratory can be time-consuming and frustrating. Here, we describe the Golgi-Cox staining in such detail that should turn the staining into an easily feasible method for all scientists working in the neuroscience field. PMID:27065817
Lee, Myung Hee; Liu, Yufeng
2013-12-01
The continuum regression technique provides an appealing regression framework connecting ordinary least squares, partial least squares and principal component regression in one family. It offers some insight on the underlying regression model for a given application. Moreover, it helps to provide deep understanding of various regression techniques. Despite the useful framework, however, the current development on continuum regression is only for linear regression. In many applications, nonlinear regression is necessary. The extension of continuum regression from linear models to nonlinear models using kernel learning is considered. The proposed kernel continuum regression technique is quite general and can handle very flexible regression model estimation. An efficient algorithm is developed for fast implementation. Numerical examples have demonstrated the usefulness of the proposed technique. PMID:24058224
Towards a universal barcode of oomycetes--a comparison of the cox1 and cox2 loci.
Choi, Young-Joon; Beakes, Gordon; Glockling, Sally; Kruse, Julia; Nam, Bora; Nigrelli, Lisa; Ploch, Sebastian; Shin, Hyeon-Dong; Shivas, Roger G; Telle, Sabine; Voglmayr, Hermann; Thines, Marco
2015-11-01
Oomycetes are a diverse group of eukaryotes in terrestrial, limnic and marine habitats worldwide and include several devastating plant pathogens, for example Phytophthora infestans (potato late blight). The cytochrome c oxidase subunit 2 gene (cox2) has been widely used for identification, taxonomy and phylogeny of various oomycete groups. However, recently the cox1 gene was proposed as a DNA barcode marker instead, together with ITS rDNA. The cox1 locus has been used in some studies of Pythium and Phytophthora, but has rarely been used for other oomycetes, as amplification success of cox1 varies with different lineages and sample ages. To determine which out of cox1 or cox2 is best suited as a universal oomycete barcode, we compared these two genes in terms of (i) PCR efficiency for 31 representative genera, as well as for historic herbarium specimens, and (ii) sequence polymorphism, intra- and interspecific divergence. The primer sets for cox2 successfully amplified all oomycete genera tested, while cox1 failed to amplify three genera. In addition, cox2 exhibited higher PCR efficiency for historic herbarium specimens, providing easier access to barcoding-type material. Sequence data for several historic type specimens exist for cox2, but there are none for cox1. In addition, cox2 yielded higher species identification success, with higher interspecific and lower intraspecific divergences than cox1. Therefore, cox2 is suggested as a partner DNA barcode along with ITS rDNA instead of cox1. The cox2-1 spacer could be a useful marker below species level. Improved protocols and universal primers are presented for all genes to facilitate future barcoding efforts. PMID:25728598
Bao, J Y
1991-04-01
The commonly used microforceps have a much greater opening distance and spring resistance than needed. A piece of plastic ring or rubber band can be used to adjust the opening distance and reduce most of the spring resistance, making the user feel more comfortable and less fatigued. PMID:2051437
Cyclooxygenase-2 (COX-2) expression in canine intracranial meningiomas.
Rossmeisl, J H; Robertson, J L; Zimmerman, K L; Higgins, M A; Geiger, D A
2009-09-01
Meningiomas are the most common canine intracranial tumour. Neurologic disability and death from treatment failure remain problematic despite current surgical and radiotherapeutic treatments for canine intracranial meningiomas. Cyclooxygenase-2 (COX-2) over-expression has been demonstrated in multiple canine malignancies, and COX-2 inhibitory treatment strategies have been shown to have both preventative and therapeutic effects in spontaneous and experimental models of cancer. The purpose of this study was to evaluate COX-2 expression in canine intracranial meningiomas. Immunohistochemical and Western blot (WB) analyses showed COX-2 expression in multiple tissues of the normal canine brain, and 87% (21/24) of intracranial meningiomas studied were immunoreactive to COX-2. No significant associations between COX-2 immunoreactivity and tumour grade were identified. Further studies are required to elucidate the physiologic roles of constitutive COX-2 expression in the central nervous system as well as its participation in meningioma tumourigenesis. PMID:19691646
Validation of a heteroscedastic hazards regression model.
Wu, Hong-Dar Isaac; Hsieh, Fushing; Chen, Chen-Hsin
2002-03-01
A Cox-type regression model accommodating heteroscedasticity, with a power factor of the baseline cumulative hazard, is investigated for analyzing data with crossing hazards behavior. Since the approach of partial likelihood cannot eliminate the baseline hazard, an overidentified estimating equation (OEE) approach is introduced in the estimation procedure. It by-product, a model checking statistic, is presented to test for the overall adequacy of the heteroscedastic model. Further, under the heteroscedastic model setting, we propose two statistics to test the proportional hazards assumption. Implementation of this model is illustrated in a data analysis of a cancer clinical trial. PMID:11878222
The Mitochondrial Genome of Conus textile, coxI-coxII Intergenic Sequences and Conoidean Evolution
Bandyopadhyay, Pradip K; Stevenson, Bradford J.; Ownby, John-Paul; Cady, Matthew T.; Watkins, Maren; Olivera, Baldomero M.
2009-01-01
The cone snails belong to the superfamily Conoidea, comprising ∼10,000 venomous marine gastropods. We determined the complete mitochondrial DNA sequence of Conus textile. The gene order is identical in Conus textile, Lophiotoma cerithiformis (another Conoidean gastropod), and the neogastropod Ilyanassa obsoleta, (not in the superfamily Conoidea). However, the intergenic interval between the coxI/coxII genes, was much longer in C. textile (165 bp) than in any other previously analyzed gastropod. We used the intergenic region to evaluate evolutionary patterns. In most neogastropods and three conidean families the intergenic interval is small (<30 nucleotides). Within Conus, the variation is from 130-170 bp, and each different clade within Conus has a narrower size distribution. In Conasprella, a subgenus traditionally assigned to Conus, the intergenic regions vary between 200-500 bp, suggesting that the species in Conasprella are not congeneric with Conus. The intergenic region was used for phylogenetic analysis of a group of fish-hunting Conus, despite the short length resolution was better than using standard markers. Thus, the coxI/coxII intergenic region can be used both to define evolutionary relationships between species in a clade, and to understand broad evolutionary patterns across the large superfamily Conoidea. PMID:17936021
Harry, Herbert H.
1989-01-01
Apparatus and method for the adjustment and alignment of shafts in high power devices. A plurality of adjacent rotatable angled cylinders are positioned between a base and the shaft to be aligned which when rotated introduce an axial offset. The apparatus is electrically conductive and constructed of a structurally rigid material. The angled cylinders allow the shaft such as the center conductor in a pulse line machine to be offset in any desired alignment position within the range of the apparatus.
Inhibition of cyclooxygenase (COX)-2 affects endothelial progenitor cell proliferation
Colleselli, Daniela; Bijuklic, Klaudija; Mosheimer, Birgit A.; Kaehler, Christian M. . E-mail: C.M.Kaehler@uibk.ac.at
2006-09-10
Growing evidence indicates that inducible cyclooxygenase-2 (COX-2) is involved in the pathogenesis of inflammatory disorders and various types of cancer. Endothelial progenitor cells recruited from the bone marrow have been shown to be involved in the formation of new vessels in malignancies and discussed for being a key point in tumour progression and metastasis. However, until now, nothing is known about an interaction between COX and endothelial progenitor cells (EPC). Expression of COX-1 and COX-2 was detected by semiquantitative RT-PCR and Western blot. Proliferation kinetics, cell cycle distribution and rate of apoptosis were analysed by MTT test and FACS analysis. Further analyses revealed an implication of Akt phosphorylation and caspase-3 activation. Both COX-1 and COX-2 expression can be found in bone-marrow-derived endothelial progenitor cells in vitro. COX-2 inhibition leads to a significant reduction in proliferation of endothelial progenitor cells by an increase in apoptosis and cell cycle arrest. COX-2 inhibition leads further to an increased cleavage of caspase-3 protein and inversely to inhibition of Akt activation. Highly proliferating endothelial progenitor cells can be targeted by selective COX-2 inhibition in vitro. These results indicate that upcoming therapy strategies in cancer patients targeting COX-2 may be effective in inhibiting tumour vasculogenesis as well as angiogenic processes.
Eberly, Lynn E
2007-01-01
This chapter describes multiple linear regression, a statistical approach used to describe the simultaneous associations of several variables with one continuous outcome. Important steps in using this approach include estimation and inference, variable selection in model building, and assessing model fit. The special cases of regression with interactions among the variables, polynomial regression, regressions with categorical (grouping) variables, and separate slopes models are also covered. Examples in microbiology are used throughout. PMID:18450050
Energy Science and Technology Software Center (ESTSC)
2015-09-09
The NCCS Regression Test Harness is a software package that provides a framework to perform regression and acceptance testing on NCCS High Performance Computers. The package is written in Python and has only the dependency of a Subversion repository to store the regression tests.
Orthogonal Regression and Equivariance.
ERIC Educational Resources Information Center
Blankmeyer, Eric
Ordinary least-squares regression treats the variables asymmetrically, designating a dependent variable and one or more independent variables. When it is not obvious how to make this distinction, a researcher may prefer to use orthogonal regression, which treats the variables symmetrically. However, the usual procedure for orthogonal regression is…
Unitary Response Regression Models
ERIC Educational Resources Information Center
Lipovetsky, S.
2007-01-01
The dependent variable in a regular linear regression is a numerical variable, and in a logistic regression it is a binary or categorical variable. In these models the dependent variable has varying values. However, there are problems yielding an identity output of a constant value which can also be modelled in a linear or logistic regression with…
Ratios as a size adjustment in morphometrics.
Albrecht, G H; Gelvin, B R; Hartman, S E
1993-08-01
Simple ratios in which a measurement variable is divided by a size variable are commonly used but known to be inadequate for eliminating size correlations from morphometric data. Deficiencies in the simple ratio can be alleviated by incorporating regression coefficients describing the bivariate relationship between the measurement and size variables. Recommendations have included: 1) subtracting the regression intercept to force the bivariate relationship through the origin (intercept-adjusted ratios); 2) exponentiating either the measurement or the size variable using an allometry coefficient to achieve linearity (allometrically adjusted ratios); or 3) both subtracting the intercept and exponentiating (fully adjusted ratios). These three strategies for deriving size-adjusted ratios imply different data models for describing the bivariate relationship between the measurement and size variables (i.e., the linear, simple allometric, and full allometric models, respectively). Algebraic rearrangement of the equation associated with each data model leads to a correctly formulated adjusted ratio whose expected value is constant (i.e., size correlation is eliminated). Alternatively, simple algebra can be used to derive an expected value function for assessing whether any proposed ratio formula is effective in eliminating size correlations. Some published ratio adjustments were incorrectly formulated as indicated by expected values that remain a function of size after ratio transformation. Regression coefficients incorporated into adjusted ratios must be estimated using least-squares regression of the measurement variable on the size variable. Use of parameters estimated by any other regression technique (e.g., major axis or reduced major axis) results in residual correlations between size and the adjusted measurement variable. Correctly formulated adjusted ratios, whose parameters are estimated by least-squares methods, do control for size correlations. The size-adjusted
JOINT STRUCTURE SELECTION AND ESTIMATION IN THE TIME-VARYING COEFFICIENT COX MODEL
Xiao, Wei; Lu, Wenbin; Zhang, Hao Helen
2016-01-01
Time-varying coefficient Cox model has been widely studied and popularly used in survival data analysis due to its flexibility for modeling covariate effects. It is of great practical interest to accurately identify the structure of covariate effects in a time-varying coefficient Cox model, i.e. covariates with null effect, constant effect and truly time-varying effect, and estimate the corresponding regression coefficients. Combining the ideas of local polynomial smoothing and group nonnegative garrote, we develop a new penalization approach to achieve such goals. Our method is able to identify the underlying true model structure with probability tending to one and simultaneously estimate the time-varying coefficients consistently. The asymptotic normalities of the resulting estimators are also established. We demonstrate the performance of our method using simulations and an application to the primary biliary cirrhosis data. PMID:27540275
Mahdi, Chanif; Nurdiana, Nurdiana; Kikuchi, Takheshi; Fatchiyah, Fatchiyah
2014-01-01
To understand the structural features that dictate the selectivity of the two isoforms of the prostaglandin H2 synthase (PGHS/COX), the three-dimensional (3D) structure of COX-1/COX-2 was assessed by means of binding energy calculation of virtual molecular dynamic with using ligand alpha-Patchouli alcohol isomers. Molecular interaction studies with COX-1 and COX-2 were done using the molecular docking tools by Hex 8.0. Interactions were further visualized by using Discovery Studio Client 3.5 software tool. The binding energy of molecular interaction was calculated by AMBER12 and Virtual Molecular Dynamic 1.9.1 software. The analysis of the alpha-Patchouli alcohol isomer compounds showed that all alpha-Patchouli alcohol isomers were suggested as inhibitor of COX-1 and COX-2. Collectively, the scoring binding energy calculation (with PBSA Model Solvent) of alpha-Patchouli alcohol isomer compounds (CID442384, CID6432585, CID3080622, CID10955174, and CID56928117) was suggested as candidate for a selective COX-1 inhibitor and CID521903 as nonselective COX-1/COX-2. PMID:25484897
Raharjo, Sentot Joko; Mahdi, Chanif; Nurdiana, Nurdiana; Kikuchi, Takheshi; Fatchiyah, Fatchiyah
2014-01-01
To understand the structural features that dictate the selectivity of the two isoforms of the prostaglandin H2 synthase (PGHS/COX), the three-dimensional (3D) structure of COX-1/COX-2 was assessed by means of binding energy calculation of virtual molecular dynamic with using ligand alpha-Patchouli alcohol isomers. Molecular interaction studies with COX-1 and COX-2 were done using the molecular docking tools by Hex 8.0. Interactions were further visualized by using Discovery Studio Client 3.5 software tool. The binding energy of molecular interaction was calculated by AMBER12 and Virtual Molecular Dynamic 1.9.1 software. The analysis of the alpha-Patchouli alcohol isomer compounds showed that all alpha-Patchouli alcohol isomers were suggested as inhibitor of COX-1 and COX-2. Collectively, the scoring binding energy calculation (with PBSA Model Solvent) of alpha-Patchouli alcohol isomer compounds (CID442384, CID6432585, CID3080622, CID10955174, and CID56928117) was suggested as candidate for a selective COX-1 inhibitor and CID521903 as nonselective COX-1/COX-2. PMID:25484897
COX, LOX and platelet aggregation inhibitory properties of Lauraceae neolignans.
Coy, Ericsson David; Cuca, Luis Enrique; Sefkow, Michael
2009-12-15
The anti-inflammatory potential of 26 neolignans (14 of the bicyclooctane-type and 12 of the benzofuran-type), isolated from three Lauraceae species (Pleurothyrium cinereum, Ocotea macrophylla and Nectandra amazonum), was evaluated in vitro through inhibition of COX-1, COX-2, 5-LOX and agonist-induced aggregation of rabbit platelets. Benzofuran neolignans were found to be selective COX-2 inhibitors, whereas bicyclooctane neolignans inhibit selectively the PAF-action as well as COX-1 and 5-LOX. The neolignan 9-nor-7,8-dehydro-isolicarin B 15 and cinerin C 7 were found to be the most potent COX-2 inhibitor and PAF-antagonist, respectively. Nectamazin C 10 exhibited dual 5-LOX/COX-2 inhibition. PMID:19880317
COX2 Inhibition Reduces Aortic Valve Calcification In Vivo
Wirrig, Elaine E.; Gomez, M. Victoria; Hinton, Robert B.; Yutzey, Katherine E.
2016-01-01
Objective Calcific aortic valve disease (CAVD) is a significant cause of morbidity and mortality, which affects approximately 1% of the US population and is characterized by calcific nodule formation and stenosis of the valve. Klotho-deficient mice were used to study the molecular mechanisms of CAVD as they develop robust aortic valve (AoV) calcification. Through microarray analysis of AoV tissues from klotho-deficient and wild type mice, increased expression of the gene encoding cyclooxygenase 2/COX2 (Ptgs2) was found. COX2 activity contributes to bone differentiation and homeostasis, thus the contribution of COX2 activity to AoV calcification was assessed. Approach and Results In klotho-deficient mice, COX2 expression is increased throughout regions of valve calcification and is induced in the valvular interstitial cells (VICs) prior to calcification formation. Similarly, COX2 expression is increased in human diseased AoVs. Treatment of cultured porcine aortic VICs with osteogenic media induces bone marker gene expression and calcification in vitro, which is blocked by inhibition of COX2 activity. In vivo, genetic loss of function of COX2 cyclooxygenase activity partially rescues AoV calcification in klotho-deficient mice. Moreover, pharmacologic inhibition of COX2 activity in klotho-deficient mice via celecoxib-containing diet reduces AoV calcification and blocks osteogenic gene expression. Conclusions COX2 expression is upregulated in CAVD and its activity contributes to osteogenic gene induction and valve calcification in vitro and in vivo. PMID:25722432
Mucin 1 Regulates Cox-2 Gene in Pancreatic Cancer
Nath, Sritama; Roy, Lopamudra Das; Grover, Priyanka; Rao, Shanti; Mukherjee, Pinku
2015-01-01
Objective Eighty percent of pancreatic ductal adenocarcinomas (PDAs) overexpress mucin 1 (MUC1), a transmembrane mucin glycoprotein. MUC1high PDA patients also express high levels of cyclooxygenase 2 (COX-2) and show poor prognosis. The cytoplasmic tail of MUC1 (MUC1-CT) partakes in oncogenic signaling, resulting in accelerated cancer progression. Our aim was to understand the regulation of Cox-2 expression by MUC1. Methods Levels of COX-2 and MUC1 were determined in MUC1−/−, MUC1low, and MUC1high PDA cells and tumors using reverse transcriptase–polymerase chain reaction, Western blot, and immunohistochemistry. Proliferative and invasive potential was assessed using MTT and Boyden chamber assays. Chromatin immunoprecipitation was performed to evaluate binding of MUC1-CT to the promoter of COX-2 gene. Results Significantly higher levels of COX-2 mRNA and protein were detected in MUC1high versus MUC1low/null cells, which were recapitulated in vivo. In addition, deletion of MUC1 gene and transient knockdown of MUC1 led to decreased COX-2 level. Also, MUC1-CT associated with the COX-2 promoter at ∼1000 base pairs upstream of the transcription start site, the same gene locus where nuclear factor κB p65 associates with the COX-2 promoter. Conclusions Data supports a novel regulation of COX-2 gene by MUC1 in PDA, the intervention of which may lead to a better therapeutic targeting in PDA patients. PMID:26035123
Bareth, Bettina; Dennerlein, Sven; Mick, David U.; Nikolov, Miroslav; Urlaub, Henning
2013-01-01
Cox1, the core subunit of the cytochrome c oxidase, receives two heme a cofactors during assembly of the 13-subunit enzyme complex. However, at which step of the assembly process and how heme is inserted into Cox1 have remained an enigma. Shy1, the yeast SURF1 homolog, has been implicated in heme transfer to Cox1, whereas the heme a synthase, Cox15, catalyzes the final step of heme a synthesis. Here we performed a comprehensive analysis of cytochrome c oxidase assembly intermediates containing Shy1. Our analyses suggest that Cox15 displays a role in cytochrome c oxidase assembly, which is independent of its functions as the heme a synthase. Cox15 forms protein complexes with Shy1 and also associates with Cox1-containing complexes independently of Shy1 function. These findings indicate that Shy1 does not serve as a mobile heme carrier between the heme a synthase and maturing Cox1 but rather cooperates with Cox15 for heme transfer and insertion in early assembly intermediates of cytochrome c oxidase. PMID:23979592
Harmonic regression and scale stability.
Lee, Yi-Hsuan; Haberman, Shelby J
2013-10-01
Monitoring a very frequently administered educational test with a relatively short history of stable operation imposes a number of challenges. Test scores usually vary by season, and the frequency of administration of such educational tests is also seasonal. Although it is important to react to unreasonable changes in the distributions of test scores in a timely fashion, it is not a simple matter to ascertain what sort of distribution is really unusual. Many commonly used approaches for seasonal adjustment are designed for time series with evenly spaced observations that span many years and, therefore, are inappropriate for data from such educational tests. Harmonic regression, a seasonal-adjustment method, can be useful in monitoring scale stability when the number of years available is limited and when the observations are unevenly spaced. Additional forms of adjustments can be included to account for variability in test scores due to different sources of population variations. To illustrate, real data are considered from an international language assessment. PMID:24092490
Gradus, Jaimie L; Antonsen, Sussie; Svensson, Elisabeth; Lash, Timothy L; Resick, Patricia A; Hansen, Jens Georg
2015-09-01
Longitudinal outcomes following stress or trauma diagnoses are receiving attention, yet population-based studies are few. The aims of the present cohort study were to examine the cumulative incidence of traumatic events and psychiatric diagnoses following diagnoses of severe stress and adjustment disorders categorized using International Classification of Diseases, Tenth Revision, codes and to examine associations of these diagnoses with all-cause mortality and suicide. Data came from a longitudinal cohort of all Danes who received a diagnosis of reaction to severe stress or adjustment disorders (International Classification of Diseases, Tenth Revision, code F43.x) between 1995 and 2011, and they were compared with data from a general-population cohort. Cumulative incidence curves were plotted to examine traumatic experiences and psychiatric diagnoses during the study period. A Cox proportional hazards regression model was used to examine the associations of the disorders with mortality and suicide. Participants with stress diagnoses had a higher incidence of traumatic events and psychiatric diagnoses than did the comparison group. Each disorder was associated with a higher rate of all-cause mortality than that seen in the comparison cohort, and strong associations with suicide were found after adjustment. This study provides a comprehensive assessment of the associations of stress disorders with a variety of outcomes, and we found that stress diagnoses may have long-lasting and potentially severe consequences. PMID:26243737
Prediction in Multiple Regression.
ERIC Educational Resources Information Center
Osborne, Jason W.
2000-01-01
Presents the concept of prediction via multiple regression (MR) and discusses the assumptions underlying multiple regression analyses. Also discusses shrinkage, cross-validation, and double cross-validation of prediction equations and describes how to calculate confidence intervals around individual predictions. (SLD)
Improved Regression Calibration
ERIC Educational Resources Information Center
Skrondal, Anders; Kuha, Jouni
2012-01-01
The likelihood for generalized linear models with covariate measurement error cannot in general be expressed in closed form, which makes maximum likelihood estimation taxing. A popular alternative is regression calibration which is computationally efficient at the cost of inconsistent estimation. We propose an improved regression calibration…
Gerber, Samuel; Rübel, Oliver; Bremer, Peer-Timo; Pascucci, Valerio; Whitaker, Ross T.
2012-01-01
This paper introduces a novel partition-based regression approach that incorporates topological information. Partition-based regression typically introduce a quality-of-fit-driven decomposition of the domain. The emphasis in this work is on a topologically meaningful segmentation. Thus, the proposed regression approach is based on a segmentation induced by a discrete approximation of the Morse-Smale complex. This yields a segmentation with partitions corresponding to regions of the function with a single minimum and maximum that are often well approximated by a linear model. This approach yields regression models that are amenable to interpretation and have good predictive capacity. Typically, regression estimates are quantified by their geometrical accuracy. For the proposed regression, an important aspect is the quality of the segmentation itself. Thus, this paper introduces a new criterion that measures the topological accuracy of the estimate. The topological accuracy provides a complementary measure to the classical geometrical error measures and is very sensitive to over-fitting. The Morse-Smale regression is compared to state-of-the-art approaches in terms of geometry and topology and yields comparable or improved fits in many cases. Finally, a detailed study on climate-simulation data demonstrates the application of the Morse-Smale regression. Supplementary materials are available online and contain an implementation of the proposed approach in the R package msr, an analysis and simulations on the stability of the Morse-Smale complex approximation and additional tables for the climate-simulation study. PMID:23687424
Gerber, Samuel; Rubel, Oliver; Bremer, Peer -Timo; Pascucci, Valerio; Whitaker, Ross T.
2012-01-19
This paper introduces a novel partition-based regression approach that incorporates topological information. Partition-based regression typically introduces a quality-of-fit-driven decomposition of the domain. The emphasis in this work is on a topologically meaningful segmentation. Thus, the proposed regression approach is based on a segmentation induced by a discrete approximation of the Morse–Smale complex. This yields a segmentation with partitions corresponding to regions of the function with a single minimum and maximum that are often well approximated by a linear model. This approach yields regression models that are amenable to interpretation and have good predictive capacity. Typically, regression estimates are quantified by their geometrical accuracy. For the proposed regression, an important aspect is the quality of the segmentation itself. Thus, this article introduces a new criterion that measures the topological accuracy of the estimate. The topological accuracy provides a complementary measure to the classical geometrical error measures and is very sensitive to overfitting. The Morse–Smale regression is compared to state-of-the-art approaches in terms of geometry and topology and yields comparable or improved fits in many cases. Finally, a detailed study on climate-simulation data demonstrates the application of the Morse–Smale regression. Supplementary Materials are available online and contain an implementation of the proposed approach in the R package msr, an analysis and simulations on the stability of the Morse–Smale complex approximation, and additional tables for the climate-simulation study.
Olszowski, Tomasz; Gutowska, Izabela; Baranowska-Bosiacka, Irena; Piotrowska, Katarzyna; Korbecki, Jan; Kurzawski, Mateusz; Chlubek, Dariusz
2015-06-01
The aim of this study was to examine the effects of cadmium in concentrations relevant to those detected in human serum on cyclooxygenase-1 (COX-1) and cyclooxygenase-2 (COX-2) expression at mRNA, protein, and enzyme activity levels in THP-1 macrophages. Macrophages were incubated with various cadmium chloride (CdCl2) solutions for 48 h at final concentrations of 5 nM, 20 nM, 200 nM, and 2 μM CdCl2. The mRNA expression and protein levels of COXs were analyzed with RT-PCR and Western blotting, respectively. Prostaglandin E2 (PGE2) and stable metabolite of thromboxane B2 (TXB2) concentrations in culture media were determined using ELISA method. Our study demonstrates that cadmium at the highest tested concentrations modulates COX-1 and COX-2 at mRNA level in THP-1 macrophages; however, the lower tested cadmium concentrations appear to inhibit COX-1 protein expression. PGE2 and TXB2 production is not altered by all tested Cd concentrations; however, the significant stimulation of PGE2 and TXB2 production is observed when macrophages are exposed to both cadmium and COX-2 selective inhibitor, NS-398. The stimulatory effect of cadmium on COXs at mRNA level is not reflected at protein and enzymatic activity levels, suggesting the existence of some posttranscriptional, translational, and posttranslational events that result in silencing of those genes' expression. PMID:25645360
Schmid, Matthias; Wickler, Florian; Maloney, Kelly O.; Mitchell, Richard; Fenske, Nora; Mayr, Andreas
2013-01-01
Regression analysis with a bounded outcome is a common problem in applied statistics. Typical examples include regression models for percentage outcomes and the analysis of ratings that are measured on a bounded scale. In this paper, we consider beta regression, which is a generalization of logit models to situations where the response is continuous on the interval (0,1). Consequently, beta regression is a convenient tool for analyzing percentage responses. The classical approach to fit a beta regression model is to use maximum likelihood estimation with subsequent AIC-based variable selection. As an alternative to this established - yet unstable - approach, we propose a new estimation technique called boosted beta regression. With boosted beta regression estimation and variable selection can be carried out simultaneously in a highly efficient way. Additionally, both the mean and the variance of a percentage response can be modeled using flexible nonlinear covariate effects. As a consequence, the new method accounts for common problems such as overdispersion and non-binomial variance structures. PMID:23626706
George: Gaussian Process regression
NASA Astrophysics Data System (ADS)
Foreman-Mackey, Daniel
2015-11-01
George is a fast and flexible library, implemented in C++ with Python bindings, for Gaussian Process regression useful for accounting for correlated noise in astronomical datasets, including those for transiting exoplanet discovery and characterization and stellar population modeling.
Multivariate Regression with Calibration*
Liu, Han; Wang, Lie; Zhao, Tuo
2014-01-01
We propose a new method named calibrated multivariate regression (CMR) for fitting high dimensional multivariate regression models. Compared to existing methods, CMR calibrates the regularization for each regression task with respect to its noise level so that it is simultaneously tuning insensitive and achieves an improved finite-sample performance. Computationally, we develop an efficient smoothed proximal gradient algorithm which has a worst-case iteration complexity O(1/ε), where ε is a pre-specified numerical accuracy. Theoretically, we prove that CMR achieves the optimal rate of convergence in parameter estimation. We illustrate the usefulness of CMR by thorough numerical simulations and show that CMR consistently outperforms other high dimensional multivariate regression methods. We also apply CMR on a brain activity prediction problem and find that CMR is as competitive as the handcrafted model created by human experts. PMID:25620861
Brink, Carsten; Bernchou, Uffe; Bertelsen, Anders; Hansen, Olfred; Schytte, Tine; Bentzen, Soren M.
2014-07-15
Purpose: Large interindividual variations in volume regression of non-small cell lung cancer (NSCLC) are observable on standard cone beam computed tomography (CBCT) during fractionated radiation therapy. Here, a method for automated assessment of tumor volume regression is presented and its potential use in response adapted personalized radiation therapy is evaluated empirically. Methods and Materials: Automated deformable registration with calculation of the Jacobian determinant was applied to serial CBCT scans in a series of 99 patients with NSCLC. Tumor volume at the end of treatment was estimated on the basis of the first one third and two thirds of the scans. The concordance between estimated and actual relative volume at the end of radiation therapy was quantified by Pearson's correlation coefficient. On the basis of the estimated relative volume, the patients were stratified into 2 groups having volume regressions below or above the population median value. Kaplan-Meier plots of locoregional disease-free rate and overall survival in the 2 groups were used to evaluate the predictive value of tumor regression during treatment. Cox proportional hazards model was used to adjust for other clinical characteristics. Results: Automatic measurement of the tumor regression from standard CBCT images was feasible. Pearson's correlation coefficient between manual and automatic measurement was 0.86 in a sample of 9 patients. Most patients experienced tumor volume regression, and this could be quantified early into the treatment course. Interestingly, patients with pronounced volume regression had worse locoregional tumor control and overall survival. This was significant on patient with non-adenocarcinoma histology. Conclusions: Evaluation of routinely acquired CBCT images during radiation therapy provides biological information on the specific tumor. This could potentially form the basis for personalized response adaptive therapy.
Students Speak With Gary Cox, EPIC Project Manager
From NASAâs International Space Station Mission Control Center Gary Cox EPIC Project Manager, participates in a Digital Learning Network (DLN) event with students at South Effingham Middle School...
32. SCIENTISTS ALLAN COX (SEATED), RICHARD DOELL, AND BRENT DALRYMPLE ...
32. SCIENTISTS ALLAN COX (SEATED), RICHARD DOELL, AND BRENT DALRYMPLE AT CONTROL PANEL, ABOUT 1965. - U.S. Geological Survey, Rock Magnetics Laboratory, 345 Middlefield Road, Menlo Park, San Mateo County, CA
Akasaka, Hironari; So, Shui-Ping; Ruan, Ke-He
2015-06-16
In vascular inflammation, prostaglandin E2 (PGE₂) is largely biosynthesized by microsomal PGE₂ synthase-1 (mPGES-1), competing with other downstream eicosanoid-synthesizing enzymes, such as PGIS, a synthase of a vascular protector prostacyclin (PGI₂), to isomerize the cyclooxygenase (COX)-2-derived prostaglandin H2 (PGH₂). In this study, we found that a majority of the product from the cells co-expressing human COX-2, mPGES-1, and PGIS was PGE₂. We hypothesize that the molecular and cellular mechanisms are related to the post-translational endoplasmic reticulum (ER) arrangement of those enzymes. A set of fusion enzymes, COX-2-linker [10 amino acids (aa)]-PGIS and COX-2-linker (22 amino acids)-PGIS, were created as "The Bioruler", in which the 10 and 22 amino acids are defined linkers with known helical structures and distances (14.4 and 30.8 Å, respectively). Our experiments have shown that the efficiency of PGI₂ biosynthesis was reduced when the separation distance increased from 10 to 22 amino acids. When COX-2-10aa-PGIS (with a 14.4 Å separation) was co-expressed with mPGES-1 on the ER membrane, a major product was PGE₂, but not PGI₂. However, expression of COX-2-10aa-PGIS and mPGES-1 on a separated ER with a distance of ≫30.8 Å reduced the level of PGE₂ production. These data indicated that the mPGES-1 is "complex-likely" colocalized with COX-2 within a distance of 14.4 Å. In addition, the cells co-expressing COX-1-10aa-PGIS and mPGES-1 produced PGI₂ mainly, but not PGE₂. This indicates that mPGES-1 is expressed much farther from COX-1. These findings have led to proposed models showing the different post-translational ER organization between COX-2 and COX-1 with respect to the topological arrangement of the mPGES-1 during vascular inflammation. PMID:25988363
Regression versus No Regression in the Autistic Disorder: Developmental Trajectories
ERIC Educational Resources Information Center
Bernabei, P.; Cerquiglini, A.; Cortesi, F.; D' Ardia, C.
2007-01-01
Developmental regression is a complex phenomenon which occurs in 20-49% of the autistic population. Aim of the study was to assess possible differences in the development of regressed and non-regressed autistic preschoolers. We longitudinally studied 40 autistic children (18 regressed, 22 non-regressed) aged 2-6 years. The following developmental…
Epigenetic deregulation of the COX pathway in cancer.
Cebola, Inês; Peinado, Miguel A
2012-10-01
Inflammation is a major cause of cancer and may condition its progression. The deregulation of the cyclooxygenase (COX) pathway is implicated in several pathophysiological processes, including inflammation and cancer. Although, its targeting with nonsteroidal antiinflammatory drugs (NSAIDs) and COX-2 selective inhibitors has been investigated for years with promising results at both preventive and therapeutic levels, undesirable side effects and the limited understanding of the regulation and functionalities of the COX pathway compromise a more extensive application of these drugs. Epigenetics is bringing additional levels of complexity to the understanding of basic biological and pathological processes. The deregulation of signaling and biosynthetic pathways by epigenetic mechanisms may account for new molecular targets in cancer therapeutics. Genes of the COX pathway are seldom mutated in neoplastic cells, but a large proportion of them show aberrant expression in different types of cancer. A growing body of evidence indicates that epigenetic alterations play a critical role in the deregulation of the genes of the COX pathway. This review summarizes the current knowledge on the contribution of epigenetic processes to the deregulation of the COX pathway in cancer, getting insights into how these alterations may be relevant for the clinical management of patients. PMID:22580191
Lipid Adjustment for Chemical Exposures: Accounting for Concomitant Variables
Li, Daniel; Longnecker, Matthew P.; Dunson, David B.
2013-01-01
Background Some environmental chemical exposures are lipophilic and need to be adjusted by serum lipid levels before data analyses. There are currently various strategies that attempt to account for this problem, but all have their drawbacks. To address such concerns, we propose a new method that uses Box-Cox transformations and a simple Bayesian hierarchical model to adjust for lipophilic chemical exposures. Methods We compared our Box-Cox method to existing methods. We ran simulation studies in which increasing levels of lipid-adjusted chemical exposure did and did not increase the odds of having a disease, and we looked at both single-exposure and multiple-exposures cases. We also analyzed an epidemiology dataset that examined the effects of various chemical exposures on the risk of birth defects. Results Compared with existing methods, our Box-Cox method produced unbiased estimates, good coverage, similar power, and lower type-I error rates. This was the case in both single- and multiple-exposure simulation studies. Results from analysis of the birth-defect data differed from results using existing methods. Conclusion Our Box-Cox method is a novel and intuitive way to account for the lipophilic nature of certain chemical exposures. It addresses some of the problems with existing methods, is easily extendable to multiple exposures, and can be used in any analyses that involve concomitant variables. PMID:24051893
Practical Session: Logistic Regression
NASA Astrophysics Data System (ADS)
Clausel, M.; Grégoire, G.
2014-12-01
An exercise is proposed to illustrate the logistic regression. One investigates the different risk factors in the apparition of coronary heart disease. It has been proposed in Chapter 5 of the book of D.G. Kleinbaum and M. Klein, "Logistic Regression", Statistics for Biology and Health, Springer Science Business Media, LLC (2010) and also by D. Chessel and A.B. Dufour in Lyon 1 (see Sect. 6 of http://pbil.univ-lyon1.fr/R/pdf/tdr341.pdf). This example is based on data given in the file evans.txt coming from http://www.sph.emory.edu/dkleinb/logreg3.htm#data.
Multiple Roles of the Cox20 Chaperone in Assembly of Saccharomyces cerevisiae Cytochrome c Oxidase
Elliott, Leah E.; Saracco, Scott A.; Fox, Thomas D.
2012-01-01
The Cox2 subunit of Saccharomyces cerevisiae cytochrome c oxidase is synthesized in the mitochondrial matrix as a precursor whose leader peptide is rapidly processed by the inner membrane protease following translocation to the intermembrane space. Processing is chaperoned by Cox20, an integral inner membrane protein whose hydrophilic domains are located in the intermembrane space, and Cox20 remains associated with mature, unassembled Cox2. The Cox2 C-tail domain is exported post-translationally by the highly conserved translocase Cox18 and associated proteins. We have found that Cox20 is required for efficient export of the Cox2 C-tail. Furthermore, Cox20 interacts by co-immune precipitation with Cox18, and this interaction requires the presence of Cox2. We therefore propose that Cox20 binding to Cox2 on the trans side of the inner membrane accelerates dissociation of newly exported Cox2 from the Cox18 translocase, promoting efficient cycling of the translocase. The requirement for Cox20 in cytochrome c oxidase assembly and respiratory growth is partially bypassed by yme1, mgr1 or mgr3 mutations, each of which reduce i-AAA protease activity in the intermembrane space. Thus, Cox20 also appears to stabilize unassembled Cox2 against degradation by the i-AAA protease. Pre-Cox2 leader peptide processing by Imp1 occurs in the absence of Cox20 and i-AAA protease activity, but is greatly reduced in efficiency. Under these conditions some mature Cox2 is assembled into cytochrome c oxidase allowing weak respiratory growth. Thus, the Cox20 chaperone has important roles in leader peptide processing, C-tail export, and stabilization of Cox2. PMID:22095077
Bourens, Myriam; Boulet, Aren; Leary, Scot C.; Barrientos, Antoni
2014-01-01
Cytochrome c oxidase (CIV) deficiency is one of the most common respiratory chain defects in patients presenting with mitochondrial encephalocardiomyopathies. CIV biogenesis is complicated by the dual genetic origin of its structural subunits, and assembly of a functional holoenzyme complex requires a large number of nucleus-encoded assembly factors. In general, the functions of these assembly factors remain poorly understood, and mechanistic investigations of human CIV biogenesis have been limited by the availability of model cell lines. Here, we have used small interference RNA and transcription activator-like effector nucleases (TALENs) technology to create knockdown and knockout human cell lines, respectively, to study the function of the CIV assembly factor COX20 (FAM36A). These cell lines exhibit a severe, isolated CIV deficiency due to instability of COX2, a mitochondrion-encoded CIV subunit. Mitochondria lacking COX20 accumulate CIV subassemblies containing COX1 and COX4, similar to those detected in fibroblasts from patients carrying mutations in the COX2 copper chaperones SCO1 and SCO2. These results imply that in the absence of COX20, COX2 is inefficiently incorporated into early CIV subassemblies. Immunoprecipitation assays using a stable COX20 knockout cell line expressing functional COX20-FLAG allowed us to identify an interaction between COX20 and newly synthesized COX2. Additionally, we show that SCO1 and SCO2 act on COX20-bound COX2. We propose that COX20 acts as a chaperone in the early steps of COX2 maturation, stabilizing the newly synthesized protein and presenting COX2 to its metallochaperone module, which in turn facilitates the incorporation of mature COX2 into the CIV assembly line. PMID:24403053
Explorations in Statistics: Regression
ERIC Educational Resources Information Center
Curran-Everett, Douglas
2011-01-01
Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This seventh installment of "Explorations in Statistics" explores regression, a technique that estimates the nature of the relationship between two things for which we may only surmise a mechanistic or predictive connection.…
Modern Regression Discontinuity Analysis
ERIC Educational Resources Information Center
Bloom, Howard S.
2012-01-01
This article provides a detailed discussion of the theory and practice of modern regression discontinuity (RD) analysis for estimating the effects of interventions or treatments. Part 1 briefly chronicles the history of RD analysis and summarizes its past applications. Part 2 explains how in theory an RD analysis can identify an average effect of…
Webcast entitled Statistical Tools for Making Sense of Data, by the National Nutrient Criteria Support Center, N-STEPS (Nutrients-Scientific Technical Exchange Partnership. The section "Correlation and Regression" provides an overview of these two techniques in the context of nut...
Multiple linear regression analysis
NASA Technical Reports Server (NTRS)
Edwards, T. R.
1980-01-01
Program rapidly selects best-suited set of coefficients. User supplies only vectors of independent and dependent data and specifies confidence level required. Program uses stepwise statistical procedure for relating minimal set of variables to set of observations; final regression contains only most statistically significant coefficients. Program is written in FORTRAN IV for batch execution and has been implemented on NOVA 1200.
Mechanisms of neuroblastoma regression
Brodeur, Garrett M.; Bagatell, Rochelle
2014-01-01
Recent genomic and biological studies of neuroblastoma have shed light on the dramatic heterogeneity in the clinical behaviour of this disease, which spans from spontaneous regression or differentiation in some patients, to relentless disease progression in others, despite intensive multimodality therapy. This evidence also suggests several possible mechanisms to explain the phenomena of spontaneous regression in neuroblastomas, including neurotrophin deprivation, humoral or cellular immunity, loss of telomerase activity and alterations in epigenetic regulation. A better understanding of the mechanisms of spontaneous regression might help to identify optimal therapeutic approaches for patients with these tumours. Currently, the most druggable mechanism is the delayed activation of developmentally programmed cell death regulated by the tropomyosin receptor kinase A pathway. Indeed, targeted therapy aimed at inhibiting neurotrophin receptors might be used in lieu of conventional chemotherapy or radiation in infants with biologically favourable tumours that require treatment. Alternative approaches consist of breaking immune tolerance to tumour antigens or activating neurotrophin receptor pathways to induce neuronal differentiation. These approaches are likely to be most effective against biologically favourable tumours, but they might also provide insights into treatment of biologically unfavourable tumours. We describe the different mechanisms of spontaneous neuroblastoma regression and the consequent therapeutic approaches. PMID:25331179
Bayesian ARTMAP for regression.
Sasu, L M; Andonie, R
2013-10-01
Bayesian ARTMAP (BA) is a recently introduced neural architecture which uses a combination of Fuzzy ARTMAP competitive learning and Bayesian learning. Training is generally performed online, in a single-epoch. During training, BA creates input data clusters as Gaussian categories, and also infers the conditional probabilities between input patterns and categories, and between categories and classes. During prediction, BA uses Bayesian posterior probability estimation. So far, BA was used only for classification. The goal of this paper is to analyze the efficiency of BA for regression problems. Our contributions are: (i) we generalize the BA algorithm using the clustering functionality of both ART modules, and name it BA for Regression (BAR); (ii) we prove that BAR is a universal approximator with the best approximation property. In other words, BAR approximates arbitrarily well any continuous function (universal approximation) and, for every given continuous function, there is one in the set of BAR approximators situated at minimum distance (best approximation); (iii) we experimentally compare the online trained BAR with several neural models, on the following standard regression benchmarks: CPU Computer Hardware, Boston Housing, Wisconsin Breast Cancer, and Communities and Crime. Our results show that BAR is an appropriate tool for regression tasks, both for theoretical and practical reasons. PMID:23665468
Cardiovascular hazard of selective COX-2 inhibitors: myth or reality?
Chiolero, Arnaud; Maillard, Marc P; Burnier, Michel
2002-05-01
Since 1998, two selective inhibitors of COX-2 have been approved in many countries for the treatment of rheumatoid arthritis, osteoarthritis and acute pain. These new drugs have a significantly reduced gastrointestinal toxicity when compared with non-selective COX inhibitors. However, the results of two large clinical trials conducted in patients with osteoarthritis and rheumatoid arthritis have recently raised some concerns regarding the cardiovascular safety of these new drugs. The purpose of this paper is to review the potential mechanisms whereby selective COX-2 inhibitors could increase the cardiovascular risk of patients and to analyse the data indicating that this clinical risk indeed exists. The authors' analysis shows that even though there are pathophysiological mechanisms which could explain why selective COX-2 inhibition might increase the cardiovascular risk in patients, the actual level of evidence demonstrating that the risk is indeed increased is weak. Because of the importance of the issue, additional studies must be conducted with this class of agents. Meanwhile, it is crucial to emphasise that neither selective COX-2 inhibitors nor conventional NSAIDs replace aspirin in patients with a high cardiovascular risk. PMID:12904159
Isoxazole-Based-Scaffold Inhibitors Targeting Cyclooxygenases (COXs).
Perrone, Maria Grazia; Vitale, Paola; Panella, Andrea; Ferorelli, Savina; Contino, Marialessandra; Lavecchia, Antonio; Scilimati, Antonio
2016-06-01
A new set of cyclooxygenase (COX) inhibitors endowed with an additional functionality was explored. These new compounds also contained either rhodamine 6G or 6,7-dimethoxy-1,2,3,4-tetrahydroisoquinoline, two moieties typical of efflux pump substrates and inhibitors, respectively. Among all the synthesized compounds, two new COX inhibitors with opposite selectivity were discovered: compound 8 [N-(9-{2-[(4-{2-[3-(5-chlorofuran-2-yl)-4-phenylisoxazol-5-yl]acetamido}butyl)carbamoyl]phenyl-6-(ethylamino)-2,7-dimethyl-3H-xanthen-3-ylidene}ethanaminium chloride] was found to be a selective COX-1 inhibitor, whereas 17 (2-[3,4-bis(4-methoxyphenyl)isoxazol-5-yl]-1-[6,7-dimethoxy-3,4-dihydroisoquinolin-2-(1H)-yl]ethanone) was found to be a sub-micromolar selective COX-2 inhibitor. However, both were shown to interact with P-glycoprotein. Docking experiments helped to clarify the molecular aspects of the observed COX selectivity. PMID:27136372
Park, Sun Ah; Chevallier, Nathalie; Tejwani, Karishma; Hung, Mary M; Maruyama, Hiroko; Golde, Todd E; Koo, Edward H
2016-09-01
Epidemiologic studies indicate that chronic use of non-steroidal anti-inflammatory drugs (NSAIDs) is associated with a lower risk for developing Alzheimer's disease (AD). Because the primary mode of action of NSAIDs is to inhibit cyclooxygenase (COX) activity, it has been proposed that perturbed activity of COX-1 or COX-2 contributes to AD pathogenesis. To test the role of COX-1 or COX-2 in amyloid deposition and amyloid-associated inflammatory changes, we examined amyloid precursor protein (APP) transgenic mice in the context of either COX-1 or COX-2 deficiency. Our studies showed that loss of either COX-1 or COX-2 gene did not alter amyloid burden in brains of the APP transgenic mice. However, one marker of microglial activation (CD45) was decreased in brains of COX-1 deficient/APP animals and showed a strong trend in reduction in COX-2 deficient/APP animals. These results suggest that COX activity and amyloid deposition in brain are likely independent processes. Further, if NSAIDs do causally reduce the risks of AD, then our findings indicate that the mechanisms are likely not due primarily to their inhibition on COX or γ-secretase modulation activity, the latter reported recently after acute dosing of ibuprofen in humans and nonhuman primates. PMID:27425247
Ridge Regression: A Regression Procedure for Analyzing Correlated Independent Variables.
ERIC Educational Resources Information Center
Rakow, Ernest A.
Ridge regression is presented as an analytic technique to be used when predictor variables in a multiple linear regression situation are highly correlated, a situation which may result in unstable regression coefficients and difficulties in interpretation. Ridge regression avoids the problem of selection of variables that may occur in stepwise…
Ridge Regression Signal Processing
NASA Technical Reports Server (NTRS)
Kuhl, Mark R.
1990-01-01
The introduction of the Global Positioning System (GPS) into the National Airspace System (NAS) necessitates the development of Receiver Autonomous Integrity Monitoring (RAIM) techniques. In order to guarantee a certain level of integrity, a thorough understanding of modern estimation techniques applied to navigational problems is required. The extended Kalman filter (EKF) is derived and analyzed under poor geometry conditions. It was found that the performance of the EKF is difficult to predict, since the EKF is designed for a Gaussian environment. A novel approach is implemented which incorporates ridge regression to explain the behavior of an EKF in the presence of dynamics under poor geometry conditions. The basic principles of ridge regression theory are presented, followed by the derivation of a linearized recursive ridge estimator. Computer simulations are performed to confirm the underlying theory and to provide a comparative analysis of the EKF and the recursive ridge estimator.
Fast Censored Linear Regression
HUANG, YIJIAN
2013-01-01
Weighted log-rank estimating function has become a standard estimation method for the censored linear regression model, or the accelerated failure time model. Well established statistically, the estimator defined as a consistent root has, however, rather poor computational properties because the estimating function is neither continuous nor, in general, monotone. We propose a computationally efficient estimator through an asymptotics-guided Newton algorithm, in which censored quantile regression methods are tailored to yield an initial consistent estimate and a consistent derivative estimate of the limiting estimating function. We also develop fast interval estimation with a new proposal for sandwich variance estimation. The proposed estimator is asymptotically equivalent to the consistent root estimator and barely distinguishable in samples of practical size. However, computation time is typically reduced by two to three orders of magnitude for point estimation alone. Illustrations with clinical applications are provided. PMID:24347802
The effects of the Cox maze procedure on atrial function
Voeller, Rochus K.; Zierer, Andreas; Lall, Shelly C.; Sakamoto, Shun–ichiro; Chang, Nai–Lun; Schuessler, Richard B.; Moon, Marc R.; Damiano, Ralph J.
2010-01-01
Objective The effects of the Cox maze procedure on atrial function remain poorly defined. The purpose of this study was to investigate the effects of a modified Cox maze procedure on left and right atrial function in a porcine model. Methods After cardiac magnetic resonance imaging, 6 pigs underwent pericardiotomy (sham group), and 6 pigs underwent a modified Cox maze procedure (maze group) with bipolar radiofrequency ablation. The maze group had preablation and immediate postablation left and right atrial pressure–volume relations measured with conductance catheters. All pigs survived for 30 days. Magnetic resonance imaging was then repeated for both groups, and conductance catheter measurements were repeated for the right atrium in the maze group. Results Both groups had significantly higher left atrial volumes postoperatively. Magnetic resonance imaging–derived reservoir and booster pump functional parameters were reduced postoperatively for both groups, but there was no difference in these parameters between the groups. The maze group had significantly higher reduction in the medial and lateral left atrial wall contraction postoperatively. There was no change in immediate left atrial elastance or in the early and 30-day right atrial elastance after the Cox maze procedure. Although the initial left atrial stiffness increased after ablation, right atrial diastolic stiffness did not change initially or at 30 days. Conclusions Performing a pericardiotomy alone had a significant effect on atrial function that can be quantified by means of magnetic resonance imaging. The effects of the Cox maze procedure on left atrial function could only be detected by analyzing segmental wall motion. Understanding the precise physiologic effects of the Cox maze procedure on atrial function will help in developing less-damaging lesion sets for the surgical treatment of atrial fibrillation. PMID:19026812
Nagatsuka, Kazuyuki; Miyata, Shigeki; Kada, Akiko; Kawamura, Atsushi; Nakagawara, Jyoji; Furui, Eisuke; Takiuchi, Shin; Taomoto, Katsushi; Kario, Kazuomi; Uchiyama, Shinichiro; Saito, Kozue; Nagao, Takehiko; Kitagawa, Kazuo; Hosomi, Naohisa; Tanaka, Keiji; Kaikita, Koichi; Katayama, Yasuo; Abumiya, Takeo; Nakane, Hiroshi; Wada, Hideo; Hattori, Akira; Kimura, Kazumi; Isshiki, Takaaki; Nishikawa, Masakatsu; Yamawaki, Takemori; Yonemoto, Naohiro; Okada, Hiromi; Ogawa, Hisao; Minematsu, Kazuo; Miyata, Toshiyuki
2016-08-01
Several studies have indicated that approximately 25 % of patients treated with aspirin exhibit high on-treatment platelet reactivity (HTPR), which is potentially associated with cardiovascular events (CVEs). However, this association is still controversial, since the mechanisms by which HTPR contributes to CVEs remain unclear and a no standardised definition of HTPR has been established. To determine whether HTPR is associated with CVE recurrence and what type of assay would best predict CVE recurrence, we conducted a multicentre prospective cohort study of 592 stable cardiovascular outpatients treated with aspirin monotherapy for secondary prevention. Their HTPR was determined by arachidonic acid- or collagen-induced aggregation assays using two different agonist concentrations. Residual cyclooxygenase (COX)-1 activity was assessed by measuring serum thromboxane (TX)B2 or urinary 11-dehydro TXB2. Shear-induced platelet thrombus formation was also examined. We followed all patients for two years to evaluate how these seven indexes were related to the recurrence of CVEs (cerebral infarction, transient ischaemic attack, myocardial infarction, unstable angina, revascularisation, other arterial thrombosis, or cardiovascular death). Of 583 patients eligible for the analysis, CVEs occurred in 69 (11.8 %). A Cox regression model identified several classical risk factors associated with CVEs. However, neither HTPR nor high residual COX-1 activity was significantly associated with CVEs, even by applying cut-off values suggested in previous reports or a receiver-operating characteristic analysis. In conclusion, recurrence of CVEs occurred independently of HTPR and residual COX-1 activity. Thus, our findings do not support the use of platelet or COX-1 functional testing for predicting clinical outcomes in stable cardiovascular patients. PMID:27098431
COX-2 and PGE2-dependent immunomodulation in breast cancer.
Chen, Edward P; Smyth, Emer M
2011-11-01
COX-derived prostanoids play multiple roles in inflammation and cancer. This review highlights research examining COX-2 and PGE(2)-dependent regulation of immune cell polarization and function within the tumor microenvironment, particularly as it pertains to breast cancer. Appreciating PGE(2)-mediated immunomodulation is important in understanding how tumors evade immune surveillance by re-educating infiltrating inflammatory and immune cells to support tumorigenesis. Elucidation of the multiple and complex influences exerted by tumor stromal components may lead to targeted therapies in breast and other cancers that restrain microenvironmental permissiveness and maintain natural defenses against malignancies. PMID:21907301
Orthogonal Regression: A Teaching Perspective
ERIC Educational Resources Information Center
Carr, James R.
2012-01-01
A well-known approach to linear least squares regression is that which involves minimizing the sum of squared orthogonal projections of data points onto the best fit line. This form of regression is known as orthogonal regression, and the linear model that it yields is known as the major axis. A similar method, reduced major axis regression, is…
Bode, Manuela; Woellhaf, Michael W.; Bohnert, Maria; van der Laan, Martin; Sommer, Frederik; Jung, Martin; Zimmermann, Richard; Schroda, Michael; Herrmann, Johannes M.
2015-01-01
Members of the twin Cx9C protein family constitute the largest group of proteins in the intermembrane space (IMS) of mitochondria. Despite their conserved nature and their essential role in the biogenesis of the respiratory chain, the molecular function of twin Cx9C proteins is largely unknown. We performed a SILAC-based quantitative proteomic analysis to identify interaction partners of the conserved twin Cx9C protein Cox19. We found that Cox19 interacts in a dynamic manner with Cox11, a copper transfer protein that facilitates metalation of the Cu(B) center of subunit 1 of cytochrome c oxidase. The interaction with Cox11 is critical for the stable accumulation of Cox19 in mitochondria. Cox19 consists of a helical hairpin structure that forms a hydrophobic surface characterized by two highly conserved tyrosine-leucine dipeptides. These residues are essential for Cox19 function and its specific binding to a cysteine-containing sequence in Cox11. Our observations suggest that an oxidative modification of this cysteine residue of Cox11 stimulates Cox19 binding, pointing to a redox-regulated interplay of Cox19 and Cox11 that is critical for copper transfer in the IMS and thus for biogenesis of cytochrome c oxidase. PMID:25926683
Correlation and simple linear regression.
Eberly, Lynn E
2007-01-01
This chapter highlights important steps in using correlation and simple linear regression to address scientific questions about the association of two continuous variables with each other. These steps include estimation and inference, assessing model fit, the connection between regression and ANOVA, and study design. Examples in microbiology are used throughout. This chapter provides a framework that is helpful in understanding more complex statistical techniques, such as multiple linear regression, linear mixed effects models, logistic regression, and proportional hazards regression. PMID:18450049
Incremental hierarchical discriminant regression.
Weng, Juyang; Hwang, Wey-Shiuan
2007-03-01
This paper presents incremental hierarchical discriminant regression (IHDR) which incrementally builds a decision tree or regression tree for very high-dimensional regression or decision spaces by an online, real-time learning system. Biologically motivated, it is an approximate computational model for automatic development of associative cortex, with both bottom-up sensory inputs and top-down motor projections. At each internal node of the IHDR tree, information in the output space is used to automatically derive the local subspace spanned by the most discriminating features. Embedded in the tree is a hierarchical probability distribution model used to prune very unlikely cases during the search. The number of parameters in the coarse-to-fine approximation is dynamic and data-driven, enabling the IHDR tree to automatically fit data with unknown distribution shapes (thus, it is difficult to select the number of parameters up front). The IHDR tree dynamically assigns long-term memory to avoid the loss-of-memory problem typical with a global-fitting learning algorithm for neural networks. A major challenge for an incrementally built tree is that the number of samples varies arbitrarily during the construction process. An incrementally updated probability model, called sample-size-dependent negative-log-likelihood (SDNLL) metric is used to deal with large sample-size cases, small sample-size cases, and unbalanced sample-size cases, measured among different internal nodes of the IHDR tree. We report experimental results for four types of data: synthetic data to visualize the behavior of the algorithms, large face image data, continuous video stream from robot navigation, and publicly available data sets that use human defined features. PMID:17385628
Steganalysis using logistic regression
NASA Astrophysics Data System (ADS)
Lubenko, Ivans; Ker, Andrew D.
2011-02-01
We advocate Logistic Regression (LR) as an alternative to the Support Vector Machine (SVM) classifiers commonly used in steganalysis. LR offers more information than traditional SVM methods - it estimates class probabilities as well as providing a simple classification - and can be adapted more easily and efficiently for multiclass problems. Like SVM, LR can be kernelised for nonlinear classification, and it shows comparable classification accuracy to SVM methods. This work is a case study, comparing accuracy and speed of SVM and LR classifiers in detection of LSB Matching and other related spatial-domain image steganography, through the state-of-art 686-dimensional SPAM feature set, in three image sets.
A new method for dealing with measurement error in explanatory variables of regression models.
Freedman, Laurence S; Fainberg, Vitaly; Kipnis, Victor; Midthune, Douglas; Carroll, Raymond J
2004-03-01
We introduce a new method, moment reconstruction, of correcting for measurement error in covariates in regression models. The central idea is similar to regression calibration in that the values of the covariates that are measured with error are replaced by "adjusted" values. In regression calibration the adjusted value is the expectation of the true value conditional on the measured value. In moment reconstruction the adjusted value is the variance-preserving empirical Bayes estimate of the true value conditional on the outcome variable. The adjusted values thereby have the same first two moments and the same covariance with the outcome variable as the unobserved "true" covariate values. We show that moment reconstruction is equivalent to regression calibration in the case of linear regression, but leads to different results for logistic regression. For case-control studies with logistic regression and covariates that are normally distributed within cases and controls, we show that the resulting estimates of the regression coefficients are consistent. In simulations we demonstrate that for logistic regression, moment reconstruction carries less bias than regression calibration, and for case-control studies is superior in mean-square error to the standard regression calibration approach. Finally, we give an example of the use of moment reconstruction in linear discriminant analysis and a nonstandard problem where we wish to adjust a classification tree for measurement error in the explanatory variables. PMID:15032787
English in the National Curriculum: The Cox Report.
ERIC Educational Resources Information Center
Use of English, 1989
1989-01-01
Discusses implications of the Cox Report on English instruction in Great Britain. Questions the definitions of aims and responsibilities outlined in the report. Suggests that the magnitude of what teachers are called upon to teach and assess will diffuse rather than concentrate attention on what matters most in English as a distinctive subject.…
COX-2 inhibitors are contraindicated for treatment of combined injury.
Jiao, W; Kiang, J G; Cary, L; Elliott, T B; Pellmar, T C; Ledney, G D
2009-12-01
Casualties of radiation dispersal devices, nuclear detonation or major ionizing radiation accidents, in addition to radiation exposure, may sustain physical and/or thermal trauma. Radiation exposure plus additional tissue trauma is known as combined injury. There are no definitive therapeutic agents. Cyclooxygenase-2 (COX-2), an inducible enzyme expressed in pathological disorders and radiation injury, plays an important role in inflammation and the production of cytokines and prostaglandin E(2) (PGE(2)) and could therefore affect the outcome for victims of combined injury. The COX-2 inhibitors celecoxib and meloxicam were evaluated for their therapeutic value against combined injury in mice. In survival studies, the COX-2 inhibitors had no beneficial effect on 30-day survival, wound healing or body weight gain after radiation injury alone or after combined injury. Meloxicam accelerated death in both wounded and combined injury mice. These drugs also induced severe hepatic toxicity, exaggerated inflammatory processes, and did not enhance hematopoietic cell regeneration. This study points to potential contraindications for use of COX-2 inhibitors in patients undergoing therapy for radiation injury and combined injury. PMID:19929415
COX-2-derived endocannabinoid metabolites as novel inflammatory mediators.
Alhouayek, Mireille; Muccioli, Giulio G
2014-06-01
Cyclooxygenase-2 (COX-2) is an enzyme that plays a key role in inflammatory processes. Classically, this enzyme is upregulated in inflammatory situations and is responsible for the generation of prostaglandins (PGs) from arachidonic acid (AA). One lesser-known property of COX-2 is its ability to metabolize the endocannabinoids, N-arachidonoylethanolamine (AEA) and 2-arachidonoylglycerol (2-AG). Endocannabinoid metabolism by COX-2 is not merely a means to terminate their actions. On the contrary, it generates PG analogs, namely PG-glycerol esters (PG-G) for 2-AG and PG-ethanolamides (PG-EA or prostamides) for AEA. Although the formation of these COX-2-derived metabolites of the endocannabinoids has been known for a while, their biological effects remain to be fully elucidated. Recently, several studies have focused on the role of these PG-G or PG-EA in vivo. In this review we take a closer look at the literature concerning these novel bioactive lipids and their role in inflammation. PMID:24684963
MACRO FOR ESTIMATING THE BOX-COX POWER TRANSFORMATION
In their classic paper, Box and Cox (1964) demonstrated how a dependent variable could be transformed to satisfy simultaneously, assumptions implicit in the analysis of linear models. For the class of analyses in which the response of interest is positive and where no transformat...
On nonsingular potentials of Cox-Thompson inversion scheme
Palmai, Tamas; Apagyi, Barnabas
2010-02-15
We establish a condition for obtaining nonsingular potentials using the Cox-Thompson inverse scattering method with one phase shift. The anomalous singularities of the potentials are avoided by maintaining unique solutions of the underlying Regge-Newton integral equation for the transformation kernel. As a by-product, new inequality sequences of zeros of Bessel functions are discovered.
On nonsingular potentials of Cox-Thompson inversion scheme
NASA Astrophysics Data System (ADS)
Pálmai, Tamás; Apagyi, Barnabás
2010-02-01
We establish a condition for obtaining nonsingular potentials using the Cox-Thompson inverse scattering method with one phase shift. The anomalous singularities of the potentials are avoided by maintaining unique solutions of the underlying Regge-Newton integral equation for the transformation kernel. As a by-product, new inequality sequences of zeros of Bessel functions are discovered.
Cell-type-specific roles for COX-2 in UVB-induced skin cancer
Herschman, Harvey
2014-01-01
In human tumors, and in mouse models, cyclooxygenase-2 (COX-2) levels are frequently correlated with tumor development/burden. In addition to intrinsic tumor cell expression, COX-2 is often present in fibroblasts, myofibroblasts and endothelial cells of the tumor microenvironment, and in infiltrating immune cells. Intrinsic cancer cell COX-2 expression is postulated as only one of many sources for prostanoids required for tumor promotion/progression. Although both COX-2 inhibition and global Cox-2 gene deletion ameliorate ultraviolet B (UVB)-induced SKH-1 mouse skin tumorigenesis, neither manipulation can elucidate the cell type(s) in which COX-2 expression is required for tumorigenesis; both eliminate COX-2 activity in all cells. To address this question, we created Cox-2 flox/flox mice, in which the Cox-2 gene can be eliminated in a cell-type-specific fashion by targeted Cre recombinase expression. Cox-2 deletion in skin epithelial cells of SKH-1 Cox-2 flox/flox;K14Cre + mice resulted, following UVB irradiation, in reduced skin hyperplasia and increased apoptosis. Targeted epithelial cell Cox-2 deletion also resulted in reduced tumor incidence, frequency, size and proliferation rate, altered tumor cell differentiation and reduced tumor vascularization. Moreover, Cox-2 flox/flox;K14Cre + papillomas did not progress to squamous cell carcinomas. In contrast, Cox-2 deletion in SKH-1 Cox-2 flox/flox; LysMCre + myeloid cells had no effect on UVB tumor induction. We conclude that (i) intrinsic epithelial COX-2 activity plays a major role in UVB-induced skin cancer, (ii) macrophage/myeloid COX-2 plays no role in UVB-induced skin cancer and (iii) either there may be another COX-2-dependent prostanoid source(s) that drives UVB skin tumor induction or there may exist a COX-2-independent pathway(s) to UVB-induced skin cancer. PMID:24469308
Kirkby, Nicholas S.; Lundberg, Martina H.; Wright, William R.; Warner, Timothy D.; Paul-Clark, Mark J.; Mitchell, Jane A.
2014-01-01
Cyxlo-oxygenase (COX)-2 inhibitors, including traditional nonsteroidal anti-inflammatory drugs (NSAIDs) are associated with increased cardiovascular side effects, including myocardial infarction. We and others have shown that COX-1 and not COX-2 drives vascular prostacyclin in the healthy cardiovascular system, re-opening the question of how COX-2 might regulate cardiovascular health. In diseased, atherosclerotic vessels, the relative contribution of COX-2 to prostacyclin formation is not clear. Here we have used apoE−/−/COX-2−/− mice to show that, whilst COX-2 profoundly limits atherosclerosis, this protection is independent of local prostacyclin release. These data further illustrate the need to look for new explanations, targets and pathways to define the COX/NSAID/cardiovascular risk axis. Gene expression profiles in tissues from apoE−/−/COX-2−/− mice showed increased lymphocyte pathways that were validated by showing increased T-lymphocytes in plaques and elevated plasma Th1-type cytokines. In addition, we identified a novel target gene, rgl1, whose expression was strongly reduced by COX-2 deletion across all examined tissues. This study is the first to demonstrate that COX-2 protects vessels against atherosclerotic lesions independently of local vascular prostacyclin and uses systems biology approaches to identify new mechanisms relevant to development of next generation NSAIDs. PMID:24887395
Dewi, Lestari
2016-01-01
Introduction: The enzyme cyclooxygenase (COX) is an enzyme that catalyzes the formation of one of the mediators of inflammation, the prostaglandins. Inhibition of COX allegedly can improve inflammation-induced pathological conditions. Aim: The purpose of the present study was to evaluate the potential of Sargassum sp. components, Fucoidan and alginate, as COX inhibitors. Material and methods: The study was conducted by means of a computational (in silico) method. It was performed in two main stages, the docking between COX-1 and COX-2 with Fucoidan, alginate and aspirin (for comparison) and the analysis of the amount of interactions formed and the residues directly involved in the process of interaction. Results: Our results showed that both Fucoidan and alginate had an excellent potential as inhibitors of COX-1 and COX-2. Fucoidan had a better potential as an inhibitor of COX than alginate. COX inhibition was expected to provide a more favorable effect on inflammation-related pathological conditions. Conclusion: The active compounds Fucoidan and alginate derived from Sargassum sp. were suspected to possess a good potential as inhibitors of COX-1 and COX-2. PMID:27594740
NASA Technical Reports Server (NTRS)
Kuhl, Mark R.
1990-01-01
Current navigation requirements depend on a geometric dilution of precision (GDOP) criterion. As long as the GDOP stays below a specific value, navigation requirements are met. The GDOP will exceed the specified value when the measurement geometry becomes too collinear. A new signal processing technique, called Ridge Regression Processing, can reduce the effects of nearly collinear measurement geometry; thereby reducing the inflation of the measurement errors. It is shown that the Ridge signal processor gives a consistently better mean squared error (MSE) in position than the Ordinary Least Mean Squares (OLS) estimator. The applicability of this technique is currently being investigated to improve the following areas: receiver autonomous integrity monitoring (RAIM), coverage requirements, availability requirements, and precision approaches.
Kim, Sungduk; Chen, Ming-Hui; Ibrahim, Joseph G.; Shah, Arvind K.; Lin, Jianxin
2013-01-01
In this paper, we propose a class of Box-Cox transformation regression models with multidimensional random effects for analyzing multivariate responses for individual patient data (IPD) in meta-analysis. Our modeling formulation uses a multivariate normal response meta-analysis model with multivariate random effects, in which each response is allowed to have its own Box-Cox transformation. Prior distributions are specified for the Box-Cox transformation parameters as well as the regression coefficients in this complex model, and the Deviance Information Criterion (DIC) is used to select the best transformation model. Since the model is quite complex, a novel Monte Carlo Markov chain (MCMC) sampling scheme is developed to sample from the joint posterior of the parameters. This model is motivated by a very rich dataset comprising 26 clinical trials involving cholesterol lowering drugs where the goal is to jointly model the three dimensional response consisting of Low Density Lipoprotein Cholesterol (LDL-C), High Density Lipoprotein Cholesterol (HDL-C), and Triglycerides (TG) (LDL-C, HDL-C, TG). Since the joint distribution of (LDL-C, HDL-C, TG) is not multivariate normal and in fact quite skewed, a Box-Cox transformation is needed to achieve normality. In the clinical literature, these three variables are usually analyzed univariately: however, a multivariate approach would be more appropriate since these variables are correlated with each other. A detailed analysis of these data is carried out using the proposed methodology. PMID:23580436
Schmidtmann, I; Elsäßer, A; Weinmann, A; Binder, H
2014-12-30
For determining a manageable set of covariates potentially influential with respect to a time-to-event endpoint, Cox proportional hazards models can be combined with variable selection techniques, such as stepwise forward selection or backward elimination based on p-values, or regularized regression techniques such as component-wise boosting. Cox regression models have also been adapted for dealing with more complex event patterns, for example, for competing risks settings with separate, cause-specific hazard models for each event type, or for determining the prognostic effect pattern of a variable over different landmark times, with one conditional survival model for each landmark. Motivated by a clinical cancer registry application, where complex event patterns have to be dealt with and variable selection is needed at the same time, we propose a general approach for linking variable selection between several Cox models. Specifically, we combine score statistics for each covariate across models by Fisher's method as a basis for variable selection. This principle is implemented for a stepwise forward selection approach as well as for a regularized regression technique. In an application to data from hepatocellular carcinoma patients, the coupled stepwise approach is seen to facilitate joint interpretation of the different cause-specific Cox models. In conditional survival models at landmark times, which address updates of prediction as time progresses and both treatment and other potential explanatory variables may change, the coupled regularized regression approach identifies potentially important, stably selected covariates together with their effect time pattern, despite having only a small number of events. These results highlight the promise of the proposed approach for coupling variable selection between Cox models, which is particularly relevant for modeling for clinical cancer registries with their complex event patterns. PMID:25345575
Computing measures of explained variation for logistic regression models.
Mittlböck, M; Schemper, M
1999-01-01
The proportion of explained variation (R2) is frequently used in the general linear model but in logistic regression no standard definition of R2 exists. We present a SAS macro which calculates two R2-measures based on Pearson and on deviance residuals for logistic regression. Also, adjusted versions for both measures are given, which should prevent the inflation of R2 in small samples. PMID:10195643
Recursive Algorithm For Linear Regression
NASA Technical Reports Server (NTRS)
Varanasi, S. V.
1988-01-01
Order of model determined easily. Linear-regression algorithhm includes recursive equations for coefficients of model of increased order. Algorithm eliminates duplicative calculations, facilitates search for minimum order of linear-regression model fitting set of data satisfactory.
ADJUSTABLE DOUBLE PULSE GENERATOR
Gratian, J.W.; Gratian, A.C.
1961-08-01
>A modulator pulse source having adjustable pulse width and adjustable pulse spacing is described. The generator consists of a cross coupled multivibrator having adjustable time constant circuitry in each leg, an adjustable differentiating circuit in the output of each leg, a mixing and rectifying circuit for combining the differentiated pulses and generating in its output a resultant sequence of negative pulses, and a final amplifying circuit for inverting and square-topping the pulses. (AEC)
Adjustable sutures in children.
Engel, J Mark; Guyton, David L; Hunter, David G
2014-06-01
Although adjustable sutures are considered a standard technique in adult strabismus surgery, most surgeons are hesitant to attempt the technique in children, who are believed to be unlikely to cooperate for postoperative assessment and adjustment. Interest in using adjustable sutures in pediatric patients has increased with the development of surgical techniques specific to infants and children. This workshop briefly reviews the literature supporting the use of adjustable sutures in children and presents the approaches currently used by three experienced strabismus surgeons. PMID:24924284
The Arabidopsis COX11 Homolog is Essential for Cytochrome c Oxidase Activity
Radin, Ivan; Mansilla, Natanael; Rödel, Gerhard; Steinebrunner, Iris
2015-01-01
Members of the ubiquitous COX11 (cytochrome c oxidase 11) protein family are involved in copper delivery to the COX complex. In this work, we characterize the Arabidopsis thaliana COX11 homolog (encoded by locus At1g02410). Western blot analyses and confocal microscopy identified Arabidopsis COX11 as an integral mitochondrial protein. Despite sharing high sequence and structural similarities, the Arabidopsis COX11 is not able to functionally replace the Saccharomyces cerevisiae COX11 homolog. Nevertheless, further analysis confirmed the hypothesis that Arabidopsis COX11 is essential for COX activity. Disturbance of COX11 expression through knockdown (KD) or overexpression (OE) affected COX activity. In KD lines, the activity was reduced by ~50%, resulting in root growth inhibition, smaller rosettes and leaf curling. In OE lines, the reduction was less pronounced (~80% of the wild type), still resulting in root growth inhibition. Additionally, pollen germination was impaired in COX11 KD and OE plants. This effect on pollen germination can only partially be attributed to COX deficiency and may indicate a possible auxiliary role of COX11 in ROS metabolism. In agreement with its role in energy production, the COX11 promoter is highly active in cells and tissues with high-energy demand for example shoot and root meristems, or vascular tissues of source and sink organs. In COX11 KD lines, the expression of the plasma-membrane copper transporter COPT2 and of several copper chaperones was altered, indicative of a retrograde signaling pathway pertinent to copper homeostasis. Based on our data, we postulate that COX11 is a mitochondrial chaperone, which plays an important role for plant growth and pollen germination as an essential COX complex assembly factor. PMID:26734017
The Arabidopsis COX11 Homolog is Essential for Cytochrome c Oxidase Activity.
Radin, Ivan; Mansilla, Natanael; Rödel, Gerhard; Steinebrunner, Iris
2015-01-01
Members of the ubiquitous COX11 (cytochrome c oxidase 11) protein family are involved in copper delivery to the COX complex. In this work, we characterize the Arabidopsis thaliana COX11 homolog (encoded by locus At1g02410). Western blot analyses and confocal microscopy identified Arabidopsis COX11 as an integral mitochondrial protein. Despite sharing high sequence and structural similarities, the Arabidopsis COX11 is not able to functionally replace the Saccharomyces cerevisiae COX11 homolog. Nevertheless, further analysis confirmed the hypothesis that Arabidopsis COX11 is essential for COX activity. Disturbance of COX11 expression through knockdown (KD) or overexpression (OE) affected COX activity. In KD lines, the activity was reduced by ~50%, resulting in root growth inhibition, smaller rosettes and leaf curling. In OE lines, the reduction was less pronounced (~80% of the wild type), still resulting in root growth inhibition. Additionally, pollen germination was impaired in COX11 KD and OE plants. This effect on pollen germination can only partially be attributed to COX deficiency and may indicate a possible auxiliary role of COX11 in ROS metabolism. In agreement with its role in energy production, the COX11 promoter is highly active in cells and tissues with high-energy demand for example shoot and root meristems, or vascular tissues of source and sink organs. In COX11 KD lines, the expression of the plasma-membrane copper transporter COPT2 and of several copper chaperones was altered, indicative of a retrograde signaling pathway pertinent to copper homeostasis. Based on our data, we postulate that COX11 is a mitochondrial chaperone, which plays an important role for plant growth and pollen germination as an essential COX complex assembly factor. PMID:26734017
Analysis of COX2 mutants reveals cytochrome oxidase subassemblies in yeast
2005-01-01
Cytochrome oxidase catalyses the reduction of oxygen to water. The mitochondrial enzyme contains up to 13 subunits, 11 in yeast, of which three, Cox1p, Cox2p and Cox3p, are mitochondrially encoded. The assembly pathway of this complex is still poorly understood. Its study in yeast has been so far impeded by the rapid turnover of unassembled subunits of the enzyme. In the present study, immunoblot analysis of blue native gels of yeast wild-type and Cox2p mutants revealed five cytochrome oxidase complexes or subcomplexes: a, b, c, d and f; a is likely to be the fully assembled enzyme; b lacks Cox6ap; d contains Cox7p and/or Cox7ap; f represents unassembled Cox1p; and c, observed only in the Cox2p mutants, contains Cox1p, Cox3p, Cox5p and Cox6p and lacks the other subunits. The identification of these novel cytochrome oxidase subcomplexes should encourage the reexamination of other yeast mutants. PMID:15921494
Multinomial logistic regression ensembles.
Lee, Kyewon; Ahn, Hongshik; Moon, Hojin; Kodell, Ralph L; Chen, James J
2013-05-01
This article proposes a method for multiclass classification problems using ensembles of multinomial logistic regression models. A multinomial logit model is used as a base classifier in ensembles from random partitions of predictors. The multinomial logit model can be applied to each mutually exclusive subset of the feature space without variable selection. By combining multiple models the proposed method can handle a huge database without a constraint needed for analyzing high-dimensional data, and the random partition can improve the prediction accuracy by reducing the correlation among base classifiers. The proposed method is implemented using R, and the performance including overall prediction accuracy, sensitivity, and specificity for each category is evaluated on two real data sets and simulation data sets. To investigate the quality of prediction in terms of sensitivity and specificity, the area under the receiver operating characteristic (ROC) curve (AUC) is also examined. The performance of the proposed model is compared to a single multinomial logit model and it shows a substantial improvement in overall prediction accuracy. The proposed method is also compared with other classification methods such as the random forest, support vector machines, and random multinomial logit model. PMID:23611203
Bayesian Spatial Quantile Regression
Reich, Brian J.; Fuentes, Montserrat; Dunson, David B.
2013-01-01
Tropospheric ozone is one of the six criteria pollutants regulated by the United States Environmental Protection Agency under the Clean Air Act and has been linked with several adverse health effects, including mortality. Due to the strong dependence on weather conditions, ozone may be sensitive to climate change and there is great interest in studying the potential effect of climate change on ozone, and how this change may affect public health. In this paper we develop a Bayesian spatial model to predict ozone under different meteorological conditions, and use this model to study spatial and temporal trends and to forecast ozone concentrations under different climate scenarios. We develop a spatial quantile regression model that does not assume normality and allows the covariates to affect the entire conditional distribution, rather than just the mean. The conditional distribution is allowed to vary from site-to-site and is smoothed with a spatial prior. For extremely large datasets our model is computationally infeasible, and we develop an approximate method. We apply the approximate version of our model to summer ozone from 1997–2005 in the Eastern U.S., and use deterministic climate models to project ozone under future climate conditions. Our analysis suggests that holding all other factors fixed, an increase in daily average temperature will lead to the largest increase in ozone in the Industrial Midwest and Northeast. PMID:23459794
Bayesian Spatial Quantile Regression.
Reich, Brian J; Fuentes, Montserrat; Dunson, David B
2011-03-01
Tropospheric ozone is one of the six criteria pollutants regulated by the United States Environmental Protection Agency under the Clean Air Act and has been linked with several adverse health effects, including mortality. Due to the strong dependence on weather conditions, ozone may be sensitive to climate change and there is great interest in studying the potential effect of climate change on ozone, and how this change may affect public health. In this paper we develop a Bayesian spatial model to predict ozone under different meteorological conditions, and use this model to study spatial and temporal trends and to forecast ozone concentrations under different climate scenarios. We develop a spatial quantile regression model that does not assume normality and allows the covariates to affect the entire conditional distribution, rather than just the mean. The conditional distribution is allowed to vary from site-to-site and is smoothed with a spatial prior. For extremely large datasets our model is computationally infeasible, and we develop an approximate method. We apply the approximate version of our model to summer ozone from 1997-2005 in the Eastern U.S., and use deterministic climate models to project ozone under future climate conditions. Our analysis suggests that holding all other factors fixed, an increase in daily average temperature will lead to the largest increase in ozone in the Industrial Midwest and Northeast. PMID:23459794
Luo, Chongliang; Liu, Jin; Dey, Dipak K; Chen, Kun
2016-07-01
In many fields, multi-view datasets, measuring multiple distinct but interrelated sets of characteristics on the same set of subjects, together with data on certain outcomes or phenotypes, are routinely collected. The objective in such a problem is often two-fold: both to explore the association structures of multiple sets of measurements and to develop a parsimonious model for predicting the future outcomes. We study a unified canonical variate regression framework to tackle the two problems simultaneously. The proposed criterion integrates multiple canonical correlation analysis with predictive modeling, balancing between the association strength of the canonical variates and their joint predictive power on the outcomes. Moreover, the proposed criterion seeks multiple sets of canonical variates simultaneously to enable the examination of their joint effects on the outcomes, and is able to handle multivariate and non-Gaussian outcomes. An efficient algorithm based on variable splitting and Lagrangian multipliers is proposed. Simulation studies show the superior performance of the proposed approach. We demonstrate the effectiveness of the proposed approach in an [Formula: see text] intercross mice study and an alcohol dependence study. PMID:26861909
Some functional limit theorems for compound Cox processes
NASA Astrophysics Data System (ADS)
Korolev, Victor Yu.; Chertok, A. V.; Korchagin, A. Yu.; Kossova, E. V.; Zeifman, Alexander I.
2016-06-01
An improved version of the functional limit theorem is proved establishing weak convergence of random walks generated by compound doubly stochastic Poisson processes (compound Cox processes) to Lévy processes in the Skorokhod space under more realistic moment conditions. As corollaries, theorems are proved on convergence of random walks with jumps having finite variances to Lévy processes with variance-mean mixed normal distributions, in particular, to stable Lévy processes.
Mani, Kalaivani; Dwivedi, Sada Nand; Pandey, Ravindra Mohan
2012-01-01
Objectives In India there has been a decline in overall under-five mortality, with some states still showing very high mortality rates. It is argued that there is family clustering in mortality among children aged <5 years. We explored the effects of programmable (proximate) determinants on under-five mortality by accounting for family-level clustering and adjusting for background variables using Cox frailty model in rural Empowered Action Group states (EAG) in India and compared results with standard models. Methods Analysis included 13,785 live births that occurred five years preceding the National Family Health Survey-3 (2005-06). The Cox frailty model and the traditional Cox proportional hazards models were used. Results The Cox frailty model showed that mother’s age at birth, place of delivery, sex of the baby, composite variable of birth order and birth interval, baby size at birth, and breastfeeding were significant determinants of under-five mortality, after adjusting for the familial frailty effect. The hazard ratio was 1.41 (95% CI=1.14−1.75) for children born to mothers aged 12-19 years compared to mothers aged 20-30 years, 1.42 (95% CI=1.12−1.79) for small-sized than average-sized babies at birth, and 102 (95% CI=81−128) for non-breastfed than breastfed babies. Children had significantly lower mortality risks in the richest than poorest wealth quintile. The familial frailty effect was 2.86 in the rural EAG states. The hazard ratios for the determinants in all the three models were similar except the death of a previous child variable in the Cox frailty model, which had the highest R2 and lowest log-likelihood. Conclusions and Public Health Implications While planning for the child survival program in rural EAG states, parental competence which explains the unobserved familial effect needs to be considered along with significant programmable determinants. The frailty models that provide statistically valid estimates of the covariate effects are
Linear regression in astronomy. I
NASA Technical Reports Server (NTRS)
Isobe, Takashi; Feigelson, Eric D.; Akritas, Michael G.; Babu, Gutti Jogesh
1990-01-01
Five methods for obtaining linear regression fits to bivariate data with unknown or insignificant measurement errors are discussed: ordinary least-squares (OLS) regression of Y on X, OLS regression of X on Y, the bisector of the two OLS lines, orthogonal regression, and 'reduced major-axis' regression. These methods have been used by various researchers in observational astronomy, most importantly in cosmic distance scale applications. Formulas for calculating the slope and intercept coefficients and their uncertainties are given for all the methods, including a new general form of the OLS variance estimates. The accuracy of the formulas was confirmed using numerical simulations. The applicability of the procedures is discussed with respect to their mathematical properties, the nature of the astronomical data under consideration, and the scientific purpose of the regression. It is found that, for problems needing symmetrical treatment of the variables, the OLS bisector performs significantly better than orthogonal or reduced major-axis regression.
Psychological Adjustment in Young Korean American Adolescents and Parental Warmth
Kim, Eunjung
2008-01-01
Problem: The relation between parental warmth and psychological adjustment is not known for young Korean American adolescents. Methods: 103 adolescents' perceived parental warmth and psychological adjustment were assessed using, respectively, the Parental Acceptance-Rejection Questionnaire and the Child Personality Assessment Questionnaire. Findings: Low perceived maternal and paternal warmth were positively related to adolescents' overall poor psychological adjustment and almost all of its attributes. When maternal and paternal warmth were entered simultaneously into the regression equation, only low maternal warmth was related to adolescents' poor psychological adjustment. Conclusion: Perceived parental warmth is important in predicting young adolescents' psychological adjustment as suggested in the parental acceptance-rejection theory. PMID:19885379
[New studies of COX-inhibitors, yet issues remain].
Wollheim, Frank A
2003-09-18
Advantages and risks related to the use of selective COX-2 inhibitors when treating arthritis are currently being scrutinized by authorities and public. The discussion tends towards exaggerated claims for or against their usefulness. The issue of cardiovascular safety is still not finally settled. In an experimental study using patients with severe coronary disease, administration of celecoxib resulted in improved endothelial function together with reduced CRP levels. Gastrointestinal tolerance was studied in patients who had recently recovered from peptic ulcer bleeding. In this group of high risk patients, celecoxib was as safe as combined therapy using omeprazol and diclofenac when given for 6 months. However, both COX inhibitors caused hypertension and adverse renal effects. The second generation of selective inhibitors is being launched. Etoricoxib--related to rofecoxib--was shown to be as potent as indomethacin in the treatment of acute gout, but it caused fewer adverse reactions. In general, however, any advantage of second generation as compared to first generation COX-2 inhibitors remains to be proven. The Swedish Council on Technology Assessment in Health Care, in its "SBU Alert", has published an appraisal of celecoxib and rofecoxib, in which the need for further long-term safety studies is emphasized. PMID:14558211
Association Between COX-2 Polymorphisms and Lung Cancer Risk
Wang, Weiwei; Fan, Xinyun; Zhang, Yong; Yang, Yi; Yang, Siyuan; Li, Gaofeng
2015-01-01
Background Multiple relevant risk factors for lung cancer have been reported in different populations, but results of previous studies were not consistent. Therefore, a meta-analysis is necessary to summarize these outcomes and reach a relatively comprehensive conclusion. Material/Methods STATA 12.0 software was used for all statistical of the relationship between COX-2 polymorphisms and lung cancer risk. Inter-study heterogeneity was examined with the Q statistic (significance level at P<0.1). The publication bias among studies in the meta-analysis was analyzed with Begg’s funnel plot and Egger’s test. Hardy-Weinberg equilibrium was tested in all controls of the studies. Results COX-2 rs20417 polymorphism had a significant association with reduced risk of lung cancer under homozygous and recessive models, and similar results were observed in white and population-based subgroups under 2 and 3 contrasts, respectively. Additionally, rs2066826 polymorphism manifested a strong correlation with increased risk of lung cancer under 5 genetic models. Conclusions In COX-2 gene, rs20417 may have a certain relationship with reduced risk of lung cancer, while rs2066826 may increase the risk of lung cancer. PMID:26624903
Risk-adjusted monitoring of survival times
Sego, Landon H.; Reynolds, Marion R.; Woodall, William H.
2009-02-26
We consider the monitoring of clinical outcomes, where each patient has a di®erent risk of death prior to undergoing a health care procedure.We propose a risk-adjusted survival time CUSUM chart (RAST CUSUM) for monitoring clinical outcomes where the primary endpoint is a continuous, time-to-event variable that may be right censored. Risk adjustment is accomplished using accelerated failure time regression models. We compare the average run length performance of the RAST CUSUM chart to the risk-adjusted Bernoulli CUSUM chart, using data from cardiac surgeries to motivate the details of the comparison. The comparisons show that the RAST CUSUM chart is more efficient at detecting a sudden decrease in the odds of death than the risk-adjusted Bernoulli CUSUM chart, especially when the fraction of censored observations is not too high. We also discuss the implementation of a prospective monitoring scheme using the RAST CUSUM chart.
2011-01-01
Background Increased cyclooxygenase activity promotes progression of colorectal cancer, but the mechanisms behind COX-2 induction remain elusive. This study was therefore aimed to define external cell signaling and transcription factors relating to high COX-2 expression in colon cancer tissue. Method Tumor and normal colon tissue were collected at primary curative operation in 48 unselected patients. COX-2 expression in tumor and normal colon tissue was quantified including microarray analyses on tumor mRNA accounting for high and low tumor COX-2 expression. Cross hybridization was performed between tumor and normal colon tissue. Methylation status of up-stream COX-2 promoter region was evaluated. Results Tumors with high COX-2 expression displayed large differences in gene expression compared to normal colon. Numerous genes with altered expression appeared in tumors of high COX-2 expression compared to tumors of low COX-2. COX-2 expression in normal colon was increased in patients with tumors of high COX-2 compared to normal colon from patients with tumors of low COX-2. IL1β, IL6 and iNOS transcripts were up-regulated among external cell signaling factors; nine transcription factors (ATF3, C/EBP, c-Fos, Fos-B, JDP2, JunB, c-Maf, NF-κB, TCF4) showed increased expression and 5 (AP-2, CBP, Elk-1, p53, PEA3) were decreased in tumors with high COX-2. The promoter region of COX-2 gene did not show consistent methylation in tumor or normal colon tissue. Conclusions Transcription and external cell signaling factors are altered as covariates to COX-2 expression in colon cancer tissue, but DNA methylation of the COX-2 promoter region was not a significant factor behind COX-2 expression in tumor and normal colon tissue. PMID:21668942
Evaluating differential effects using regression interactions and regression mixture models
Van Horn, M. Lee; Jaki, Thomas; Masyn, Katherine; Howe, George; Feaster, Daniel J.; Lamont, Andrea E.; George, Melissa R. W.; Kim, Minjung
2015-01-01
Research increasingly emphasizes understanding differential effects. This paper focuses on understanding regression mixture models, a relatively new statistical methods for assessing differential effects by comparing results to using an interactive term in linear regression. The research questions which each model answers, their formulation, and their assumptions are compared using Monte Carlo simulations and real data analysis. The capabilities of regression mixture models are described and specific issues to be addressed when conducting regression mixtures are proposed. The paper aims to clarify the role that regression mixtures can take in the estimation of differential effects and increase awareness of the benefits and potential pitfalls of this approach. Regression mixture models are shown to be a potentially effective exploratory method for finding differential effects when these effects can be defined by a small number of classes of respondents who share a typical relationship between a predictor and an outcome. It is also shown that the comparison between regression mixture models and interactions becomes substantially more complex as the number of classes increases. It is argued that regression interactions are well suited for direct tests of specific hypotheses about differential effects and regression mixtures provide a useful approach for exploring effect heterogeneity given adequate samples and study design. PMID:26556903
Supercomplex-associated Cox26 protein binds to cytochrome c oxidase.
Strecker, Valentina; Kadeer, Zibirnisa; Heidler, Juliana; Cruciat, Cristina-Maria; Angerer, Heike; Giese, Heiko; Pfeiffer, Kathy; Stuart, Rosemary A; Wittig, Ilka
2016-07-01
Here we identified a hydrophobic 6.4kDa protein, Cox26, as a novel component of yeast mitochondrial supercomplex comprising respiratory complexes III and IV. Multi-dimensional native and denaturing electrophoretic techniques were used to identify proteins interacting with Cox26. The majority of the Cox26 protein was found non-covalently bound to the complex IV moiety of the III-IV supercomplexes. A population of Cox26 was observed to exist in a disulfide bond partnership with the Cox2 subunit of complex IV. No pronounced growth phenotype for Cox26 deficiency was observed, indicating that Cox26 may not play a critical role in the COX enzymology, and we speculate that Cox26 may serve to regulate or support the Cox2 protein. Respiratory supercomplexes are assembled in the absence of the Cox26 protein, however their pattern slightly differs to the wild type III-IV supercomplex appearance. The catalytic activities of complexes III and IV were observed to be normal and respiration was comparable to wild type as long as cells were cultivated under normal growth conditions. Stress conditions, such as elevated temperatures resulted in mild decrease of respiration in non-fermentative media when the Cox26 protein was absent. PMID:27091403
Upregulation of fibronectin expression by COX-2 is mediated by interaction with ELMO1.
Yang, Chen; Sorokin, Andrey
2011-01-01
Engulfment and cell motility 1 (ELMO1), a bipartite guanine nucleotide exchange factor (GEF) for the small GTPase Rac 1, was identified as a susceptibility gene for glomerular disease. Here, we reported that ELMO1 interacted with COX-2 in human mesangial cells. Furthermore, we identified ELMO1 as a posttranslational regulator of COX-2 activity. We demonstrated that COX-2 cyclooxygenase activity increased fibronectin promoter activity. The protein-protein interaction between ELMO1 and COX-2 increased the cyclooxygenase activity of COX-2 and, correspondingly, fibronectin expression. We also found that ET625, the dominant negative form of ELMO1 lacking Rac1 activity, interacted with COX-2, increased cyclooxygenase activity of COX-2 and enhanced COX-2-mediated fibronectin upregulation. To further rule out Rac1 as an ELMO1-mediated regulator of COX-2 activity, we employed the constitutive active Rac1, Rac1(Q63E), and demonstrated that Rac1 signaling has no effect on COX-2-mediated fibronectin promoter activity. These results suggest that ELMO1 contributes to the development of glomerular injury through serving as a regulator of COX-2 activity. The interaction of ELMO1 with COX-2 could play an important role in the development and progression of renal glomerular injury. PMID:20732417
Naoi, Kazuhisa; Kogure, Suguru; Saito, Masataka; Hamazaki, Tomohito; Watanabe, Shiro
2006-07-01
We have shown that anorexic response is induced by intraperitoneal injection of zymosan in mice, although the role of prostaglandins in this response is relatively unknown as compared with lipopolysaccharide (LPS)-induced anorexic response. Indomethacin (0.5 and 2.0 mg/kg), a non-selective cyclooxygenase (COX) inhibitor, as well as meloxicam (0.5 mg/kg), a selective COX-2 inhibitor, but not FR122047 (2.0 mg/kg), a selective COX-1 inhibitor, attenuated zymosan-induced anorexia. Zymosan injection elevated COX-2 expression in brain and liver but not in small intestine and colon. Meloxicam (0.5 mg/kg) and FR122047 treatment (2.0 mg/kg) similarly suppressed the generation of brain prostaglandin E(2) (PGE(2)) and peritoneal prostacyclin (PGI(2)) upon zymosan injection. PGE(2) generation in liver upon zymosan injection was suppressed by meloxicam (0.5 mg/kg) but not by FR122047 treatment (2.0 mg/kg). Our observations suggest that COX-2 plays an important role in zymosan-induced anorexia, which is a similar feature in LPS-induced anorexic response. However, non-selective inhibition by selective COX-1 and COX-2 inhibitors of brain PGE(2) generation upon zymosan injection does not support the role of COX-2 expressed in brain in zymosan-induced anorexic response. PGE(2) generation in liver may account for peripheral role of COX-2 in zymosan-induced anorexic response. PMID:16819161
Linear regression in astronomy. II
NASA Technical Reports Server (NTRS)
Feigelson, Eric D.; Babu, Gutti J.
1992-01-01
A wide variety of least-squares linear regression procedures used in observational astronomy, particularly investigations of the cosmic distance scale, are presented and discussed. The classes of linear models considered are (1) unweighted regression lines, with bootstrap and jackknife resampling; (2) regression solutions when measurement error, in one or both variables, dominates the scatter; (3) methods to apply a calibration line to new data; (4) truncated regression models, which apply to flux-limited data sets; and (5) censored regression models, which apply when nondetections are present. For the calibration problem we develop two new procedures: a formula for the intercept offset between two parallel data sets, which propagates slope errors from one regression to the other; and a generalization of the Working-Hotelling confidence bands to nonstandard least-squares lines. They can provide improved error analysis for Faber-Jackson, Tully-Fisher, and similar cosmic distance scale relations.
Quantile regression for climate data
NASA Astrophysics Data System (ADS)
Marasinghe, Dilhani Shalika
Quantile regression is a developing statistical tool which is used to explain the relationship between response and predictor variables. This thesis describes two examples of climatology using quantile regression.Our main goal is to estimate derivatives of a conditional mean and/or conditional quantile function. We introduce a method to handle autocorrelation in the framework of quantile regression and used it with the temperature data. Also we explain some properties of the tornado data which is non-normally distributed. Even though quantile regression provides a more comprehensive view, when talking about residuals with the normality and the constant variance assumption, we would prefer least square regression for our temperature analysis. When dealing with the non-normality and non constant variance assumption, quantile regression is a better candidate for the estimation of the derivative.
Transfer Learning Based on Logistic Regression
NASA Astrophysics Data System (ADS)
Paul, A.; Rottensteiner, F.; Heipke, C.
2015-08-01
In this paper we address the problem of classification of remote sensing images in the framework of transfer learning with a focus on domain adaptation. The main novel contribution is a method for transductive transfer learning in remote sensing on the basis of logistic regression. Logistic regression is a discriminative probabilistic classifier of low computational complexity, which can deal with multiclass problems. This research area deals with methods that solve problems in which labelled training data sets are assumed to be available only for a source domain, while classification is needed in the target domain with different, yet related characteristics. Classification takes place with a model of weight coefficients for hyperplanes which separate features in the transformed feature space. In term of logistic regression, our domain adaptation method adjusts the model parameters by iterative labelling of the target test data set. These labelled data features are iteratively added to the current training set which, at the beginning, only contains source features and, simultaneously, a number of source features are deleted from the current training set. Experimental results based on a test series with synthetic and real data constitutes a first proof-of-concept of the proposed method.
Evaluating Differential Effects Using Regression Interactions and Regression Mixture Models
ERIC Educational Resources Information Center
Van Horn, M. Lee; Jaki, Thomas; Masyn, Katherine; Howe, George; Feaster, Daniel J.; Lamont, Andrea E.; George, Melissa R. W.; Kim, Minjung
2015-01-01
Research increasingly emphasizes understanding differential effects. This article focuses on understanding regression mixture models, which are relatively new statistical methods for assessing differential effects by comparing results to using an interactive term in linear regression. The research questions which each model answers, their…
Retro-regression--another important multivariate regression improvement.
Randić, M
2001-01-01
We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA. PMID:11410035
The Role of Prostaglandins and COX-Enzymes in Chondrogenic Differentiation of ATDC5 Progenitor Cells
Caron, Marjolein M. J.; Emans, Pieter J.; Sanen, Kathleen; Surtel, Don A. M.; Cremers, Andy; Ophelders, Daan; van Rhijn, Lodewijk W.; Welting, Tim J. M.
2016-01-01
Objectives NSAIDs are used to relieve pain and decrease inflammation by inhibition of cyclooxygenase (COX)-catalyzed prostaglandin (PG) synthesis. PGs are fatty acid mediators involved in cartilage homeostasis, however the action of their synthesizing COX-enzymes in cartilage differentiation is not well understood. In this study we hypothesized that COX-1 and COX-2 have differential roles in chondrogenic differentiation. Methods ATDC5 cells were differentiated in the presence of COX-1 (SC-560, Mofezolac) or COX-2 (NS398, Celecoxib) specific inhibitors. Specificity of the NSAIDs and inhibition of specific prostaglandin levels were determined by EIA. Prostaglandins were added during the differentiation process. Chondrogenic outcome was determined by gene- and protein expression analyses. Results Inhibition of COX-1 prevented Col2a1 and Col10a1 expression. Inhibition of COX-2 resulted in decreased Col10a1 expression, while Col2a1 remained unaffected. To explain this difference expression patterns of both COX-enzymes as well as specific prostaglandin concentrations were determined. Both COX-enzymes are upregulated during late chondrogenic differentiation, whereas only COX-2 is briefly expressed also early in differentiation. PGD2 and PGE2 followed the COX-2 expression pattern, whereas PGF2α and TXA2 levels remained low. Furthermore, COX inhibition resulted in decreased levels of all tested PGs, except for PGD2 and PGF2α in the COX-1 inhibited condition. Addition of PGE2 and PGF2α resulted in increased expression of chondrogenic markers, whereas TXA2 increased expression of hypertrophic markers. Conclusions Our findings point towards a differential role for COX-enzymes and PG-production in chondrogenic differentiation of ATDC5 cells. Ongoing research is focusing on further elucidating the functional partition of cyclooxygenases and specific prostaglandin production. PMID:27050768
ERIC Educational Resources Information Center
Shih, Ching-Lin; Liu, Tien-Hsiang; Wang, Wen-Chung
2014-01-01
The simultaneous item bias test (SIBTEST) method regression procedure and the differential item functioning (DIF)-free-then-DIF strategy are applied to the logistic regression (LR) method simultaneously in this study. These procedures are used to adjust the effects of matching true score on observed score and to better control the Type I error…
Watanabe, K I; Ohama, T
2001-01-01
In the unicellular green alga, Chlamydomonas reinhardtii, cytochrome oxidase subunit 2 (cox2) and 3 (cox3) genes are missing from the mitochondrial genome. We isolated and sequenced a BAC clone that carries the whole cox3 gene and its corresponding cDNA. Almost the entire cox2 gene and its cDNA were also determined. Comparison of the genomic and the corresponding cDNA sequences revealed that the cox3 gene contains as many as nine spliceosomal introns and that cox2 bears six introns. Putative mitochondria targeting signals were predicted at each N terminal of the cox genes. These spliceosomal introns were typical GT-AG-type introns, which are very common not only in Chlamydomonas nuclear genes but also in diverse eukaryotic taxa. We found no particular distinguishing features in the cox introns. Comparative analysis of these genes with the various mitochondrial genes showed that 8 of the 15 introns were interrupting the conserved mature protein coding segments, while the other 7 introns were located in the N-terminal target peptide regions. Phylogenetic analysis of the evolutionary position of C. reinhardtii in Chlorophyta was carried out and the existence of the cox2 and cox3 genes in the mitochondrial genome was superimposed in the tree. This analysis clearly shows that these cox genes were relocated during the evolution of Chlorophyceae. It is apparent that long before the estimated period of relocation of these mitochondrial genes, the cytosol had lost the splicing ability for group II introns. Therefore, at least eight introns located in the mature protein coding region cannot be the direct descendant of group II introns. Here, we conclude that the presence of these introns is due to the invasion of spliceosomal introns, which occurred during the evolution of Chlorophyceae. This finding provides concrete evidence supporting the "intron-late" model, which rests largely on the mobility of spliceosomal introns. PMID:11675593
Bootstrapping a change-point Cox model for survival data.
Xu, Gongjun; Sen, Bodhisattva; Ying, Zhiliang
2014-08-20
This paper investigates the (in)-consistency of various bootstrap methods for making inference on a change-point in time in the Cox model with right censored survival data. A criterion is established for the consistency of any bootstrap method. It is shown that the usual nonparametric bootstrap is inconsistent for the maximum partial likelihood estimation of the change-point. A new model-based bootstrap approach is proposed and its consistency established. Simulation studies are carried out to assess the performance of various bootstrap schemes. PMID:25400719
Room temperature ferromagnetic (Fe₁-xCox)₃BO₅ nanorods.
He, Shuli; Zhang, Hongwang; Xing, Hui; Li, Kai; Cui, Hongfei; Yang, Chenguang; Sun, Shouheng; Zeng, Hao
2014-07-01
Cobalt-doped ferroferriborate ((Fe1-xCox)3BO5) nanorods (NRs) are synthesized by a one-pot high-temperature organic-solution-phase method. The aspect ratios of the NRs are tuned by the heating rate. These NRs form via anisotropic growth along twin boundaries of the multiply twinned nuclei. Magnetic properties are dramatically modified by Co substitutional doping, changing from antiferromagnetic order at low temperatures to ferromagnetic above room temperature, with a greatly enhanced magnetic ordering temperature. These anisotropic ferromagnetic NRs with a high ordering temperature may provide a new platform for understanding nanomagnetism and for magnetic applications. PMID:24905634
Electron paramagnetic resonance in Zn1-xCoxO
NASA Astrophysics Data System (ADS)
Acosta-Humánez, F.; Cogollo Pitalúa, R.; Almanza, O.
2013-03-01
In this paper is reported the Electron Paramagnetic Resonance (EPR) studies in Zn1-xCoxO powder, with 0.01≤x≤0.05, at many temperatures (105-250 K). These samples were synthesized by the sol-gel method (citrate route). Results suggest that the ferromagnetism behavior of the materials is governed by ferromagnetic coupling among cobalt ions. For cobalt concentration higher than 3% were obtained mean size particle higher than 25 nm, measured by X-ray diffraction, and for this were also observed shallow free radical.
Cox26 is a novel stoichiometric subunit of the yeast cytochrome c oxidase.
Levchenko, Maria; Wuttke, Jan-Moritz; Römpler, Katharina; Schmidt, Bernhard; Neifer, Klaus; Juris, Lisa; Wissel, Mirjam; Rehling, Peter; Deckers, Markus
2016-07-01
The cytochrome c oxidase (COX) is the terminal enzyme of the respiratory chain. The complex accepts electrons from cytochrome c and passes them onto molecular oxygen. This process contributes to energy capture in the form of a membrane potential across the inner membrane. The enzyme complex assembles in a stepwise process from the three mitochondria-encoded core subunits Cox1, Cox2 and Cox3, which associate with nuclear-encoded subunits and cofactors. In the yeast Saccharomyces cerevisiae, the cytochrome c oxidase associates with the bc1-complex into supercomplexes, allowing efficient energy transduction. Here we report on Cox26 as a protein found in respiratory chain supercomplexes containing cytochrome c oxidase. Our analyses reveal Cox26 as a novel stoichiometric structural subunit of the cytochrome c oxidase. A loss of Cox26 affects cytochrome c oxidase activity and respirasome organization. PMID:27083394
Precision Efficacy Analysis for Regression.
ERIC Educational Resources Information Center
Brooks, Gordon P.
When multiple linear regression is used to develop a prediction model, sample size must be large enough to ensure stable coefficients. If the derivation sample size is inadequate, the model may not predict well for future subjects. The precision efficacy analysis for regression (PEAR) method uses a cross- validity approach to select sample sizes…
Ecological Regression and Voting Rights.
ERIC Educational Resources Information Center
Freedman, David A.; And Others
1991-01-01
The use of ecological regression in voting rights cases is discussed in the context of a lawsuit against Los Angeles County (California) in 1990. Ecological regression assumes that systematic voting differences between precincts are explained by ethnic differences. An alternative neighborhood model is shown to lead to different conclusions. (SLD)
Logistic Regression: Concept and Application
ERIC Educational Resources Information Center
Cokluk, Omay
2010-01-01
The main focus of logistic regression analysis is classification of individuals in different groups. The aim of the present study is to explain basic concepts and processes of binary logistic regression analysis intended to determine the combination of independent variables which best explain the membership in certain groups called dichotomous…
NASA Astrophysics Data System (ADS)
Koloc, Z.; Korf, J.; Kavan, P.
The adjustment (modification) deals with gear chains intermediating (transmitting) motion transfer between the sprocket wheels on parallel shafts. The purpose of the adjustments of chain gear is to remove the unwanted effects by using the chain guide on the links (sliding guide rail) ensuring a smooth fit of the chain rollers into the wheel tooth gap.
Adjustment to Recruit Training.
ERIC Educational Resources Information Center
Anderson, Betty S.
The thesis examines problems of adjustment encountered by new recruits entering the military services. Factors affecting adjustment are discussed: the recruit training staff and environment, recruit background characteristics, the military's image, the changing values and motivations of today's youth, and the recruiting process. Sources of…
Fungible weights in logistic regression.
Jones, Jeff A; Waller, Niels G
2016-06-01
In this article we develop methods for assessing parameter sensitivity in logistic regression models. To set the stage for this work, we first review Waller's (2008) equations for computing fungible weights in linear regression. Next, we describe 2 methods for computing fungible weights in logistic regression. To demonstrate the utility of these methods, we compute fungible logistic regression weights using data from the Centers for Disease Control and Prevention's (2010) Youth Risk Behavior Surveillance Survey, and we illustrate how these alternate weights can be used to evaluate parameter sensitivity. To make our work accessible to the research community, we provide R code (R Core Team, 2015) that will generate both kinds of fungible logistic regression weights. (PsycINFO Database Record PMID:26651981
[Regression grading in gastrointestinal tumors].
Tischoff, I; Tannapfel, A
2012-02-01
Preoperative neoadjuvant chemoradiation therapy is a well-established and essential part of the interdisciplinary treatment of gastrointestinal tumors. Neoadjuvant treatment leads to regressive changes in tumors. To evaluate the histological tumor response different scoring systems describing regressive changes are used and known as tumor regression grading. Tumor regression grading is usually based on the presence of residual vital tumor cells in proportion to the total tumor size. Currently, no nationally or internationally accepted grading systems exist. In general, common guidelines should be used in the pathohistological diagnostics of tumors after neoadjuvant therapy. In particularly, the standard tumor grading will be replaced by tumor regression grading. Furthermore, tumors after neoadjuvant treatment are marked with the prefix "y" in the TNM classification. PMID:22293790
Brochhausen, Christoph; Zehbe, Rolf; Gross, Ulrich; Libera, Jeanette; Schubert, Helmut; Nüsing, Rolf M; Klaus, Günter; Kirkpatrick, C James
2008-01-01
Tissue engineering of articular cartilage remains an ongoing challenge. Since tissue regeneration recapitulates ontogenetic processes the growth plate can be regarded as an innovative model to target suitable signalling molecules and growth factors for the tissue engineering of cartilage. In the present study we analysed the expression of cyclooxygenases (COX) in a short-term chondrocyte culture in gelatin-based scaffolds and in articular cartilage of rats and compared it with that in the growth plate. Our results demonstrate the strong cellular expression of COX-1 but only a focal weak expression of COX-2 in the seeded scaffolds. Articular cartilage of rats expresses homogeneously COX-1 and COX-2 with the exception of the apical cell layer. Our findings indicate a functional role of COX in the metabolism of articular chondrocytes. The expression of COX in articular cartilage and in the seeded scaffolds opens interesting perspectives to improve the proliferation and differentiation of chondrocytes in scaffold materials by addition of specific receptor ligands of the COX system. PMID:18198403
Fiumera, Heather L.; Dunham, Maitreya J.; Saracco, Scott A.; Butler, Christine A.; Kelly, Jessica A.; Fox, Thomas D.
2009-01-01
Members of the Oxa1/YidC/Alb3 family of protein translocases are essential for assembly of energy-transducing membrane complexes. In Saccharomyces cerevisiae, Oxa1 and its paralog, Cox18, are required for assembly of Cox2, a mitochondrially encoded subunit of cytochrome c oxidase. Oxa1 is known to be required for cotranslational export of the Cox2 N-terminal domain across the inner mitochondrial membrane, while Cox18 is known to be required for post-translational export of the Cox2 C-tail domain. We find that overexpression of Oxa1 does not compensate for the absence of Cox18 at the level of respiratory growth. However, it does promote some translocation of the Cox2 C-tail domain across the inner membrane and causes increased accumulation of Cox2, which remains unassembled. This result suggests that Cox18 not only translocates the C-tail, but also must deliver it in a distinct state competent for cytochrome oxidase assembly. We identified respiring mutants from a cox18Δ strain overexpressing OXA1, whose respiratory growth requires overexpression of OXA1. The recessive nuclear mutations allow some assembly of Cox2 into cytochrome c oxidase. After failing to identify these mutations by methods based on transformation, we successfully located them to MGR1 and MGR3 by comparative hybridization to whole-genome tiling arrays and microarray-assisted bulk segregant analysis followed by linkage mapping. While Mgr1 and Mgr3 are known to associate with the Yme1 mitochondrial inner membrane i-AAA protease and to participate in membrane protein degradation, their absence does not appear to stabilize Cox2 under these conditions. Instead, Yme1 probably chaperones the folding and/or assembly of Oxa1-exported Cox2 in the absence of Mrg1 or Mgr3, since respiratory growth and cytochrome c oxidase assembly in a cox18 mgr3 double-mutant strain overexpressing OXA1 is YME1 dependent. PMID:19307606
Practical Session: Simple Linear Regression
NASA Astrophysics Data System (ADS)
Clausel, M.; Grégoire, G.
2014-12-01
Two exercises are proposed to illustrate the simple linear regression. The first one is based on the famous Galton's data set on heredity. We use the lm R command and get coefficients estimates, standard error of the error, R2, residuals …In the second example, devoted to data related to the vapor tension of mercury, we fit a simple linear regression, predict values, and anticipate on multiple linear regression. This pratical session is an excerpt from practical exercises proposed by A. Dalalyan at EPNC (see Exercises 1 and 2 of http://certis.enpc.fr/~dalalyan/Download/TP_ENPC_4.pdf).
Splines for Diffeomorphic Image Regression
Singh, Nikhil; Niethammer, Marc
2016-01-01
This paper develops a method for splines on diffeomorphisms for image regression. In contrast to previously proposed methods to capture image changes over time, such as geodesic regression, the method can capture more complex spatio-temporal deformations. In particular, it is a first step towards capturing periodic motions for example of the heart or the lung. Starting from a variational formulation of splines the proposed approach allows for the use of temporal control points to control spline behavior. This necessitates the development of a shooting formulation for splines. Experimental results are shown for synthetic and real data. The performance of the method is compared to geodesic regression. PMID:25485370
McKenzie, K.R.
1959-07-01
An electrode support which permits accurate alignment and adjustment of the electrode in a plurality of planes and about a plurality of axes in a calutron is described. The support will align the slits in the electrode with the slits of an ionizing chamber so as to provide for the egress of ions. The support comprises an insulator, a leveling plate carried by the insulator and having diametrically opposed attaching screws screwed to the plate and the insulator and diametrically opposed adjusting screws for bearing against the insulator, and an electrode associated with the plate for adjustment therewith.
Kautter, John; Pope, Gregory C.
2004-01-01
The authors document the development of the CMS frailty adjustment model, a Medicare payment approach that adjusts payments to a Medicare managed care organization (MCO) according to the functional impairment of its community-residing enrollees. Beginning in 2004, this approach is being applied to certain organizations, such as Program of All-Inclusive Care for the Elderly (PACE), that specialize in providing care to the community-residing frail elderly. In the future, frailty adjustment could be extended to more Medicare managed care organizations. PMID:25372243
Regional Differences in the Neuronal Expression of Cyclooxygenase-2 (COX-2) in the Newborn Pig Brain
Oláh, Orsolya; Németh, István; Tóth-Szűki, Valéria; Bari, Ferenc; Domoki, Ferenc
2012-01-01
Cyclooxygenase (COX)-2 is the major constitutively expressed COX isoform in the newborn brain. COX-2 derived prostanoids and reactive oxygen species appear to play a major role in the mechanism of perinatal hypoxic-ischemic injury in the newborn piglet, an accepted animal model of the human term neonate. The study aimed to quantitatively determine COX-2 immunopositive neurons in different brain regions in piglets under normoxic conditions (n=15), and 4 hours after 10 min asphyxia (n=11). Asphyxia did not induce significant changes in neuronal COX-2 expression of any studied brain areas. In contrast, there was a marked regional difference in all experimental groups. Thus, significant difference was observed between fronto-parietal and temporo-occipital regions: 59±4% and 67±3% versus 41±2%* and 31±3%* respectively (mean±SEM, data are pooled from all subjects, n=26, *p<0.05, vs. fronto-parietal region). In the hippocampus, COX-2 immunopositivity was rare (highest expression in CA1 region: 14±2%). The studied subcortical areas showed negligible COX-2 staining. Our findings suggest that asphyxia does not significantly alter the pattern of neuronal COX-2 expression in the early reventilation period. Furthermore, based on the striking differences observed in cortical neuronal COX-2 distribution, the contribution of COX-2 mediated neuronal injury after asphyxia may also show region-specific differences. PMID:22829712
iNOS signaling interacts with COX-2 pathway in colonic fibroblasts.
Zhu, Yingting; Zhu, Min; Lance, Peter
2012-10-01
COX-2 and iNOS are two major inflammatory mediators implicated in colorectal inflammation and cancer. Previously, the role of colorectal fibroblasts involved in regulation of COX-2 and iNOS expression was largely ignored. In addition, the combined interaction of COX-2 and iNOS signalings and their significance in the progression of colorectal inflammation and cancer within the fibroblasts have received little investigation. To address those issues, we investigated the role of colonic fibroblasts in the regulation of COX-2 and iNOS gene expression, and explored possible mechanisms of interaction between COX-2 and iNOS signalings using a colonic CCD-18Co fibroblast line and LPS, a potential stimulator of COX-2 and iNOS. Our results clearly demonstrated that LPS activated COX-2 gene expression and enhanced PGE(2) production, stimulated iNOS gene expression and promoted NO production in the fibroblasts. Interestingly, activation of COX-2 signaling by LPS was not involved in activation of iNOS signaling, while activation of iNOS signaling by LPS contributed in part to activation of COX-2 signaling. Further analysis indicated that PKC plays a major role in the activation and interaction of COX-2 and iNOS signalings induced by LPS in the fibroblasts. PMID:22683859
Ku80 cooperates with CBP to promote COX-2 expression and tumor growth
Qin, Yu; Xuan, Yang; Jia, Yunlu; Hu, Wenxian; Yu, Wendan; Dai, Meng; Li, Zhenglin; Yi, Canhui; Zhao, Shilei; Li, Mei; Du, Sha; Cheng, Wei; Xiao, Xiangsheng; Chen, Yiming; Wu, Taihua; Meng, Songshu; Yuan, Yuhui; Liu, Quentin; Huang, Wenlin; Guo, Wei; Wang, Shusen; Deng, Wuguo
2015-01-01
Cyclooxygenase-2 (COX-2) plays an important role in lung cancer development and progression. Using streptavidin-agarose pulldown and proteomics assay, we identified and validated Ku80, a dimer of Ku participating in the repair of broken DNA double strands, as a new binding protein of the COX-2 gene promoter. Overexpression of Ku80 up-regulated COX-2 promoter activation and COX-2 expression in lung cancer cells. Silencing of Ku80 by siRNA down-regulated COX-2 expression and inhibited tumor cell growth in vitro and in a xenograft mouse model. Ku80 knockdown suppressed phosphorylation of ERK, resulting in an inactivation of the MAPK pathway. Moreover, CBP, a transcription co-activator, interacted with and acetylated Ku80 to co-regulate the activation of COX-2 promoter. Overexpression of CBP increased Ku80 acetylation, thereby promoting COX-2 expression and cell growth. Suppression of CBP by a CBP-specific inhibitor or siRNA inhibited COX-2 expression as well as tumor cell growth. Tissue microarray immunohistochemical analysis of lung adenocarcinomas revealed a strong positive correlation between levels of Ku80 and COX-2 and clinicopathologic variables. Overexpression of Ku80 was associated with poor prognosis in patients with lung cancers. We conclude that Ku80 promotes COX-2 expression and tumor growth and is a potential therapeutic target in lung cancer. PMID:25797267
COX-2 inhibitor as a radiation enhancer: new strategies for the treatment of lung cancer.
Saha, Debabrata; Pyo, Hongryull; Choy, Hak
2003-08-01
Lung cancer is one of the most common causes of cancer-related mortality throughout the world, and the incidence continues to increase. Smoking is the number one cause of lung cancer. Emerging data have implicated cyclooxygenase-2 (COX-2) and prostanoid production in the pathogenesis of lung carcinoma. In invasive lung tumors, COX-2 upregulation has been reported in up to 90% of cases. COX-2 upregulation is an early event in the development of non-small-cell lung cancer and may be integral to the development of new blood vessels and production of specific proteases that are critical to growth and spread of lung malignancies. COX-2 inhibitors are known to enhance the chemosensitivity in COX-2 overexpressing lung cancer cell lines. Recently, we have demonstrated that selective COX-2 inhibitors also enhance the effect of radiation in COX-2 overexpressed cells. Therefore, inhibitors of COX-2 in combination with chemoradiation therapy may be an alternative strategy that can be tested in clinical trials. The combination of COX-2 inhibitors and radiation suggest a complementary strategy to target angiogenesis while potentially minimizing the impact on quality of life. Currently, several groups are conducting clinical trials in cervix cancer, lung cancer, and brain tumors, using inhibitors of COX-2 in combination with chemotherapy and radiation therapy. These clinical trials will help to elucidate the role of this interesting class. PMID:12902860
The cytochrome c oxidase biogenesis factor AtCOX17 modulates stress responses in Arabidopsis.
Garcia, Lucila; Welchen, Elina; Gey, Uta; Arce, Agustín L; Steinebrunner, Iris; Gonzalez, Daniel H
2016-03-01
COX17 is a soluble protein from the mitochondrial intermembrane space that participates in the transfer of copper for cytochrome c oxidase (COX) assembly in eukaryotic organisms. In this work, we studied the function of both Arabidopsis thaliana AtCOX17 genes using plants with altered expression levels of these genes. Silencing of AtCOX17-1 in a cox17-2 knockout background generates plants with smaller rosettes and decreased expression of genes involved in the response of plants to different stress conditions, including several genes that are induced by mitochondrial dysfunctions. Silencing of either of the AtCOX17 genes does not affect plant development or COX activity but causes a decrease in the response of genes to salt stress. In addition, these plants contain higher reactive oxygen and lipid peroxidation levels after irrigation with high NaCl concentrations and are less sensitive to abscisic acid. In agreement with a role of AtCOX17 in stress and abscisic acid responses, both AtCOX17 genes are induced by several stress conditions, abscisic acid and mutation of the transcription factor ABI4. The results indicate that AtCOX17 is required for optimal expression of a group of stress-responsive genes, probably as a component of signalling pathways that link stress conditions to gene expression responses. PMID:26436309
Characterization of the Cytochrome C Oxidase Assembly Factor Cox19 of 'Saccharomyces Cerevisiae'
Rigby, K.; Zhang, L.; Cobine, P.A.; George, G.N.; Winge, D.R.; /Utah U. /Saskatchewan U.
2007-07-12
Cox19 is an important accessory protein in the assembly of cytochrome c oxidase in yeast. The protein is functional when tethered to the mitochondrial inner membrane, suggesting its functional role within the intermembrane space. Cox19 resembles Cox17 in having a twin CX{sub 9}C sequence motif that adopts a helical hairpin in Cox17. The function of Cox17 appears to be a Cu(I) donor protein in the assembly of the copper centers in cytochrome c oxidase. Cox19 also resembles Cox17 in its ability to coordinate Cu(I). Recombinant Cox19 binds 1 mol eq of Cu(I) per monomer and exists as a dimeric protein. Cox19 isolated from the mitochondrial intermembrane space contains variable quantities of copper, suggesting that Cu(I) binding may be a transient property. Cysteinyl residues important for Cu(I) binding are also shown to be important for the in vivo function of Cox19. Thus, a correlation exists in the ability to bind Cu(I) and in vivo function.
Theilig, F; Debiec, H; Nafz, B; Ronco, P; Nüsing, R; Seyberth, H W; Pavenstädt, H; Bouby, N; Bachmann, S
2006-11-01
Renal volume regulation is modulated by the action of cyclooxygenases (COX) and the resulting generation of prostanoids. Epithelial expression of COX isoforms in the cortex directs COX-1 to the distal convolutions and cortical collecting duct, and COX-2 to the thick ascending limb. Partly colocalized are prostaglandin E synthase (PGES), the downstream enzyme for renal prostaglandin E(2) (PGE(2)) generation, and the EP receptors type 1 and 3. COX-1 and related components were studied in two kidney-one clip (2K1C) Goldblatt hypertensive rats with combined chronic ANG II or bradykinin B(2) receptor blockade using candesartan (cand) or the B(2) antagonist Hoechst 140 (Hoe). Rats (untreated sham, 2K1C, sham + cand, 2K1C + cand, sham + Hoe, 2K1C + Hoe) were treated to map expression of parameters controlling PGE(2) synthesis. In 2K1C, cortical COX isoforms did not change uniformly. COX-2 changed in parallel with NO synthase 1 (NOS1) expression with a raise in the clipped, but a decrease in the nonclipped side. By contrast, COX-1 and PGES were uniformly downregulated in both kidneys, along with reduced urinary PGE(2) levels, and showed no clear relations with the NO status. ANG II receptor blockade confirmed negative regulation of COX-2 by ANG II but blunted the decrease in COX-1 selectively in nonclipped kidneys. B(2) receptor blockade reduced COX-2 induction in 2K1C but had no clear effect on COX-1. We suggest that in 2K1C, COX-1 and PGES expression may fail to oppose the effects of renovascular hypertension through reduced prostaglandin signaling in late distal tubule and cortical collecting duct. PMID:16788145
Lachin, John M.
2013-01-01
Summary General expressions are described for the evaluation of sample size and power for the K group Mantel-logrank test or the Cox PH model score test. Under an exponential model, the method of Lachin and Foulkes [1] for the 2 group case is extended to the K ≥ 2 group case using the non-centrality parameter of the K – 1 df chi-square test. Similar results are also shown to apply to the K group score test in a Cox PH model. Lachin and Foulkes [1] employed a truncated exponential distribution to provide for a non-linear rate of enrollment. Expressions for the mean time of enrollment and the expected follow-up time in the presence of exponential losses-to-follow-up are presented. When used with the expression for the non-centrality parameter for the test, equations are derived for the evaluation of sample size and power under specific designs with R years of recruitment and T years total duration. Sample size and power are also described for a stratified-adjusted K group test and for the assessment of a group by stratum interaction. Similarly computations are described for a stratified-adjusted analysis of a quantitative covariate and a test of a stratum by covariate interaction in the Cox PH model. PMID:23670965
Abstract Expression Grammar Symbolic Regression
NASA Astrophysics Data System (ADS)
Korns, Michael F.
This chapter examines the use of Abstract Expression Grammars to perform the entire Symbolic Regression process without the use of Genetic Programming per se. The techniques explored produce a symbolic regression engine which has absolutely no bloat, which allows total user control of the search space and output formulas, which is faster, and more accurate than the engines produced in our previous papers using Genetic Programming. The genome is an all vector structure with four chromosomes plus additional epigenetic and constraint vectors, allowing total user control of the search space and the final output formulas. A combination of specialized compiler techniques, genetic algorithms, particle swarm, aged layered populations, plus discrete and continuous differential evolution are used to produce an improved symbolic regression sytem. Nine base test cases, from the literature, are used to test the improvement in speed and accuracy. The improved results indicate that these techniques move us a big step closer toward future industrial strength symbolic regression systems.
Multiple Regression and Its Discontents
ERIC Educational Resources Information Center
Snell, Joel C.; Marsh, Mitchell
2012-01-01
Multiple regression is part of a larger statistical strategy originated by Gauss. The authors raise questions about the theory and suggest some changes that would make room for Mandelbrot and Serendipity.
Time-Warped Geodesic Regression
Hong, Yi; Singh, Nikhil; Kwitt, Roland; Niethammer, Marc
2016-01-01
We consider geodesic regression with parametric time-warps. This allows, for example, to capture saturation effects as typically observed during brain development or degeneration. While highly-flexible models to analyze time-varying image and shape data based on generalizations of splines and polynomials have been proposed recently, they come at the cost of substantially more complex inference. Our focus in this paper is therefore to keep the model and its inference as simple as possible while allowing to capture expected biological variation. We demonstrate that by augmenting geodesic regression with parametric time-warp functions, we can achieve comparable flexibility to more complex models while retaining model simplicity. In addition, the time-warp parameters provide useful information of underlying anatomical changes as demonstrated for the analysis of corpora callosa and rat calvariae. We exemplify our strategy for shape regression on the Grassmann manifold, but note that the method is generally applicable for time-warped geodesic regression. PMID:25485368
Basis Selection for Wavelet Regression
NASA Technical Reports Server (NTRS)
Wheeler, Kevin R.; Lau, Sonie (Technical Monitor)
1998-01-01
A wavelet basis selection procedure is presented for wavelet regression. Both the basis and the threshold are selected using cross-validation. The method includes the capability of incorporating prior knowledge on the smoothness (or shape of the basis functions) into the basis selection procedure. The results of the method are demonstrated on sampled functions widely used in the wavelet regression literature. The results of the method are contrasted with other published methods.
Regression methods for spatial data
NASA Technical Reports Server (NTRS)
Yakowitz, S. J.; Szidarovszky, F.
1982-01-01
The kriging approach, a parametric regression method used by hydrologists and mining engineers, among others also provides an error estimate the integral of the regression function. The kriging method is explored and some of its statistical characteristics are described. The Watson method and theory are extended so that the kriging features are displayed. Theoretical and computational comparisons of the kriging and Watson approaches are offered.
Wrong Signs in Regression Coefficients
NASA Technical Reports Server (NTRS)
McGee, Holly
1999-01-01
When using parametric cost estimation, it is important to note the possibility of the regression coefficients having the wrong sign. A wrong sign is defined as a sign on the regression coefficient opposite to the researcher's intuition and experience. Some possible causes for the wrong sign discussed in this paper are a small range of x's, leverage points, missing variables, multicollinearity, and computational error. Additionally, techniques for determining the cause of the wrong sign are given.
Remotely Adjustable Hydraulic Pump
NASA Technical Reports Server (NTRS)
Kouns, H. H.; Gardner, L. D.
1987-01-01
Outlet pressure adjusted to match varying loads. Electrohydraulic servo has positioned sleeve in leftmost position, adjusting outlet pressure to maximum value. Sleeve in equilibrium position, with control land covering control port. For lowest pressure setting, sleeve shifted toward right by increased pressure on sleeve shoulder from servovalve. Pump used in aircraft and robots, where hydraulic actuators repeatedly turned on and off, changing pump load frequently and over wide range.
Shrinkage regression-based methods for microarray missing value imputation
2013-01-01
Background Missing values commonly occur in the microarray data, which usually contain more than 5% missing values with up to 90% of genes affected. Inaccurate missing value estimation results in reducing the power of downstream microarray data analyses. Many types of methods have been developed to estimate missing values. Among them, the regression-based methods are very popular and have been shown to perform better than the other types of methods in many testing microarray datasets. Results To further improve the performances of the regression-based methods, we propose shrinkage regression-based methods. Our methods take the advantage of the correlation structure in the microarray data and select similar genes for the target gene by Pearson correlation coefficients. Besides, our methods incorporate the least squares principle, utilize a shrinkage estimation approach to adjust the coefficients of the regression model, and then use the new coefficients to estimate missing values. Simulation results show that the proposed methods provide more accurate missing value estimation in six testing microarray datasets than the existing regression-based methods do. Conclusions Imputation of missing values is a very important aspect of microarray data analyses because most of the downstream analyses require a complete dataset. Therefore, exploring accurate and efficient methods for estimating missing values has become an essential issue. Since our proposed shrinkage regression-based methods can provide accurate missing value estimation, they are competitive alternatives to the existing regression-based methods. PMID:24565159
Background stratified Poisson regression analysis of cohort data
Langholz, Bryan
2012-01-01
Background stratified Poisson regression is an approach that has been used in the analysis of data derived from a variety of epidemiologically important studies of radiation-exposed populations, including uranium miners, nuclear industry workers, and atomic bomb survivors. We describe a novel approach to fit Poisson regression models that adjust for a set of covariates through background stratification while directly estimating the radiation-disease association of primary interest. The approach makes use of an expression for the Poisson likelihood that treats the coefficients for stratum-specific indicator variables as ‘nuisance’ variables and avoids the need to explicitly estimate the coefficients for these stratum-specific parameters. Log-linear models, as well as other general relative rate models, are accommodated. This approach is illustrated using data from the Life Span Study of Japanese atomic bomb survivors and data from a study of underground uranium miners. The point estimate and confidence interval obtained from this ‘conditional’ regression approach are identical to the values obtained using unconditional Poisson regression with model terms for each background stratum. Moreover, it is shown that the proposed approach allows estimation of background stratified Poisson regression models of non-standard form, such as models that parameterize latency effects, as well as regression models in which the number of strata is large, thereby overcoming the limitations of previously available statistical software for fitting background stratified Poisson regression models. PMID:22193911
Background stratified Poisson regression analysis of cohort data.
Richardson, David B; Langholz, Bryan
2012-03-01
Background stratified Poisson regression is an approach that has been used in the analysis of data derived from a variety of epidemiologically important studies of radiation-exposed populations, including uranium miners, nuclear industry workers, and atomic bomb survivors. We describe a novel approach to fit Poisson regression models that adjust for a set of covariates through background stratification while directly estimating the radiation-disease association of primary interest. The approach makes use of an expression for the Poisson likelihood that treats the coefficients for stratum-specific indicator variables as 'nuisance' variables and avoids the need to explicitly estimate the coefficients for these stratum-specific parameters. Log-linear models, as well as other general relative rate models, are accommodated. This approach is illustrated using data from the Life Span Study of Japanese atomic bomb survivors and data from a study of underground uranium miners. The point estimate and confidence interval obtained from this 'conditional' regression approach are identical to the values obtained using unconditional Poisson regression with model terms for each background stratum. Moreover, it is shown that the proposed approach allows estimation of background stratified Poisson regression models of non-standard form, such as models that parameterize latency effects, as well as regression models in which the number of strata is large, thereby overcoming the limitations of previously available statistical software for fitting background stratified Poisson regression models. PMID:22193911
Weighted triangulation adjustment
Anderson, Walter L.
1969-01-01
The variation of coordinates method is employed to perform a weighted least squares adjustment of horizontal survey networks. Geodetic coordinates are required for each fixed and adjustable station. A preliminary inverse geodetic position computation is made for each observed line. Weights associated with each observed equation for direction, azimuth, and distance are applied in the formation of the normal equations in-the least squares adjustment. The number of normal equations that may be solved is twice the number of new stations and less than 150. When the normal equations are solved, shifts are produced at adjustable stations. Previously computed correction factors are applied to the shifts and a most probable geodetic position is found for each adjustable station. Pinal azimuths and distances are computed. These may be written onto magnetic tape for subsequent computation of state plane or grid coordinates. Input consists of punch cards containing project identification, program options, and position and observation information. Results listed include preliminary and final positions, residuals, observation equations, solution of the normal equations showing magnitudes of shifts, and a plot of each adjusted and fixed station. During processing, data sets containing irrecoverable errors are rejected and the type of error is listed. The computer resumes processing of additional data sets.. Other conditions cause warning-errors to be issued, and processing continues with the current data set.
Krawczyk, Michal; Emerson, Beverly M
2014-01-01
Deregulated expression of COX-2 has been causally linked to development, progression, and outcome of several types of human cancer. We describe a novel fundamental level of transcriptional control of COX-2 expression. Using primary human mammary epithelial cells and monocyte/macrophage cell lines, we show that the chromatin boundary/insulator factor CTCF establishes an open chromatin domain and induces expression of a long non-coding RNA within the upstream promoter region of COX-2. Upon induction of COX-2 expression, the lncRNA associates with p50, a repressive subunit of NF-κB, and occludes it from the COX-2 promoter, potentially facilitating interaction with activation-competent NF-κB p65/p50 dimers. This enables recruitment of the p300 histone acetyltransferase, a domain-wide increase in histone acetylation and assembly of RNA Polymerase II initiation complexes. Our findings reveal an unexpected mechanism of gene control by lncRNA-mediated repressor occlusion and identify the COX-2-lncRNA, PACER, as a new potential target for COX-2-modulation in inflammation and cancer. DOI: http://dx.doi.org/10.7554/eLife.01776.001 PMID:24843008
Gaussian estimation for discretely observed Cox-Ingersoll-Ross model
NASA Astrophysics Data System (ADS)
Wei, Chao; Shu, Huisheng; Liu, Yurong
2016-07-01
This paper is concerned with the parameter estimation problem for Cox-Ingersoll-Ross model based on discrete observation. First, a new discretized process is built based on the Euler-Maruyama scheme. Then, the parameter estimators are obtained by employing the maximum likelihood method and the explicit expressions of the error of estimation are given. Subsequently, the consistency property of all parameter estimators are proved by applying the law of large numbers for martingales, Holder's inequality, B-D-G inequality and Cauchy-Schwarz inequality. Finally, a numerical simulation example for estimators and the absolute error between estimators and true values is presented to demonstrate the effectiveness of the estimation approach used in this paper.
(R)-Profens Are Substrate-Selective Inhibitors of Endocannabinoid Oxygenation by COX-2
Duggan, Kelsey C.; Hermanson, Daniel J.; Musee, Joel; Prusakiewicz, Jeffery J.; Scheib, Jami L.; Carter, Bruce D.; Banerjee, Surajit; Oates, J.A.; Marnett, Lawrence J.
2012-01-01
Cyclooxygenase-2 (COX-2) catalyzes the oxygenation of arachidonic acid and the endocannabinoids, 2-arachidonoylglycerol and arachidonoylethanolamide. Evaluation of a series of COX-2 inhibitors revealed that many weak, competitive inhibitors of arachidonic acid oxygenation are potent inhibitors of endocannabinoid oxygenation. (R)-Enantiomers of ibuprofen, naproxen, and flurbiprofen, which are considered to be inactive as COX-2 inhibitors, are potent “substrate-selective inhibitors” of endocannabinoid oxygenation. Crystal structures of the COX-2-(R)-naproxen and COX-2-(R)-flurbiprofen complexes verified this unexpected binding and defined the orientation of the (R)-enantiomers relative to (S)-enantiomers. (R)-Profens selectively inhibited endocannabinoid oxygenation by lipopolysaccharide-stimulated dorsal root ganglion cells. Substrate-selective inhibition provides novel tools for investigating the role of COX-2 in endocannabinoid oxygenation and a possible explanation for the ability of (R)-profens to maintain endocannabinoid tone in models of neuropathic pain. PMID:22053353
Box-Cox Mixed Logit Model for Travel Behavior Analysis
NASA Astrophysics Data System (ADS)
Orro, Alfonso; Novales, Margarita; Benitez, Francisco G.
2010-09-01
To represent the behavior of travelers when they are deciding how they are going to get to their destination, discrete choice models, based on the random utility theory, have become one of the most widely used tools. The field in which these models were developed was halfway between econometrics and transport engineering, although the latter now constitutes one of their principal areas of application. In the transport field, they have mainly been applied to mode choice, but also to the selection of destination, route, and other important decisions such as the vehicle ownership. In usual practice, the most frequently employed discrete choice models implement a fixed coefficient utility function that is linear in the parameters. The principal aim of this paper is to present the viability of specifying utility functions with random coefficients that are nonlinear in the parameters, in applications of discrete choice models to transport. Nonlinear specifications in the parameters were present in discrete choice theory at its outset, although they have seldom been used in practice until recently. The specification of random coefficients, however, began with the probit and the hedonic models in the 1970s, and, after a period of apparent little practical interest, has burgeoned into a field of intense activity in recent years with the new generation of mixed logit models. In this communication, we present a Box-Cox mixed logit model, original of the authors. It includes the estimation of the Box-Cox exponents in addition to the parameters of the random coefficients distribution. Probability of choose an alternative is an integral that will be calculated by simulation. The estimation of the model is carried out by maximizing the simulated log-likelihood of a sample of observed individual choices between alternatives. The differences between the predictions yielded by models that are inconsistent with real behavior have been studied with simulation experiments.
Inference of median difference based on the Box-Cox model in randomized clinical trials.
Maruo, K; Isogawa, N; Gosho, M
2015-05-10
In randomized clinical trials, many medical and biological measurements are not normally distributed and are often skewed. The Box-Cox transformation is a powerful procedure for comparing two treatment groups for skewed continuous variables in terms of a statistical test. However, it is difficult to directly estimate and interpret the location difference between the two groups on the original scale of the measurement. We propose a helpful method that infers the difference of the treatment effect on the original scale in a more easily interpretable form. We also provide statistical analysis packages that consistently include an estimate of the treatment effect, covariance adjustments, standard errors, and statistical hypothesis tests. The simulation study that focuses on randomized parallel group clinical trials with two treatment groups indicates that the performance of the proposed method is equivalent to or better than that of the existing non-parametric approaches in terms of the type-I error rate and power. We illustrate our method with cluster of differentiation 4 data in an acquired immune deficiency syndrome clinical trial. PMID:25565079
Perpendicular magnetic anisotropy in Fe2Cr1 - xCoxSi Heusler alloy
NASA Astrophysics Data System (ADS)
Wang, Yu-Pu; Qiu, Jin-Jun; Lu, Hui; Ji, Rong; Han, Gu-Chang; Teo, Kie-Leong
2014-12-01
Perpendicular magnetic anisotropy (PMA) was achieved in annealed Fe2Cr1 - xCoxSi (FCCS) Heusler alloys with different Co compositions x. The Co composition is varied to tune the Fermi level in order to achieve both higher spin polarization and better thermal stability. The PMA is thermally stable up to 400 oC for FCCS with x = 0, 0.3, 0.5 and 350 oC for FCCS with x = 0.7, 0.9, 1. The thickness of FCCS films with PMA ranges from 0.6 to 1.2 nm. The annealing temperature and FCCS thickness are found to greatly affect the PMA. The magnetic anisotropy energy density KU is 2.8 × 106 erg cm-3 for 0.8 nm Fe2CrSi, and decreases as the Co composition x increases, suggesting that the PMA induced at the FCCS/MgO interface is dominated by the contribution of Fe atoms. There is a trade-off between high spin polarization and strong PMA by adjusting the Co composition.
COX-2-mediated stimulation of the lymphangiogenic factor VEGF-C in human breast cancer
Timoshenko, A V; Chakraborty, C; Wagner, G F; Lala, P K
2006-01-01
Increased expression of COX-2 or VEGF-C has been correlated with progressive disease in certain cancers. Present study utilized several human breast cancer cell lines (MCF-7, T-47D, Hs578T and MDA-MB-231, varying in COX-2 expression) as well as 10 human breast cancer specimens to examine the roles of COX-2 and prostaglandin E (EP) receptors in VEGF-C expression or secretion, and the relationship of COX-2 or VEGF-C expression to lymphangiogenesis. We found a strong correlation between COX-2 mRNA expression and VEGF-C expression or secretion levels in breast cancer cell lines and VEGF-C expression in breast cancer tissues. Expression of LYVE-1, a selective marker for lymphatic endothelium, was also positively correlated with COX-2 or VEGF-C expression in breast cancer tissues. Inhibition of VEGF-C expression and secretion in the presence of COX-1/2 or COX-2 inhibitors or following downregulation of COX-2 with COX-2 siRNA established a stimulatory role COX-2 in VEGF-C synthesis by breast cancer cells. EP1 as well as EP4 receptor antagonists inhibited VEGF-C production indicating the roles of EP1 and EP4 in VEGF-C upregulation by endogenous PGE2. Finally, VEGF-C secretion by MDA-MB-231 cells was inhibited in the presence of kinase inhibitors for Her-2/neu, Src and p38 MAPK, indicating a requirement of these kinases for VEGF-C synthesis. These results, for the first time, demonstrate a regulatory role of COX-2 in VEGF-C synthesis (and thereby lymphangiogenesis) in human breast cancer, which is mediated at least in part by EP1/EP4 receptors. PMID:16570043
Exposure to diesel exhaust upregulates COX-2 expression in ApoE knockout mice
Bai, Ni; Tranfield, Erin M.; Kavanagh, Terrance J.; Kaufman, Joel D.; Rosenfeld, Michael E.; van Eeden, Stephan F.
2015-01-01
Introduction We have shown that diesel exhaust (DE) inhalation caused progression of atherosclerosis; however, the mechanisms are not fully understood. We hypothesize that exposure to DE upregulates cyclooxygenase (COX) expression and activity, which could play a role in DE-induced atherosclerosis. Methods ApoE knockout mice (30-week old) fed with regular chow were exposed to DE (at 200 μg/m3 of particulate matter) or filtered air (control) for 7 weeks (6 h/day, 5 days/week). The protein and mRNA expression of COX-1 and COX-2 were evaluated by immunohistochemistry analysis and quantitative real-time PCR, respectively. To examine COX activity, thoracic aortae were mounted in a wire myograph, and phenylephrine (PE)-stimulated vasoconstriction was measured with and without the presence of COX antagonists (indomethacin). COX-2 activity was further assessed by urine 2,3-dinor-6-keto PGF1α level, a major metabolite of prostacyclin I2 (PGI2). Results Immunohistochemistry analysis demonstrates that DE exposure enhanced COX-2 expression in both thoracic aorta (p < 0.01) and aortic root (p < 0.03), with no modification of COX-1 expression. The increased COX-2 expression was positively correlated with smooth muscle cell content in aortic lesions (R2 = 0.4081, p < 0.008). The fractional changes of maximal vasoconstriction in the presence of indomethacin was attenuated by 3-fold after DE exposure (p < 0.02). Urine 2,3-dinor-6-keto PGF1α level was 15-fold higher in DE group than the control (p < 0.007). The mRNA expression of COX-2 (p < 0.006) and PGI synthase (p < 0.02), but not COX-1, was significantly augmented after DE exposure. Conclusion We show that DE inhalation enhanced COX-2 expression, which is also associated with phenotypic changes of aortic lesion. PMID:22746401
Stark, David T.; Bazan, Nicolas G.
2011-01-01
Stimulation of synaptic NMDA receptors (NMDARs) induces neuroprotection, while extrasynaptic NMDARs promote excitotoxic cell death. Neuronal expression of cyclooxygenase-2 (COX-2) is enhanced by synaptic NMDARs, and although this enzyme mediates neuronal functions, COX-2 is also regarded as a key modulator of neuroinflammation and is thought to exacerbate excitotoxicity via overproduction of prostaglandins. This raises an apparent paradox: synaptic NMDARs are pro-survival yet are essential for robust neuronal COX-2 expression. We hypothesized that stimulation of extrasynaptic NMDARs converts COX-2 signaling from a physiological to a potentially pathological process. We combined HPLC-ESI-MS/MS-based mediator lipidomics and unbiased image analysis in mouse dissociated and organotypic cortical cultures to uncover that synaptic and extrasynaptic NMDARs differentially modulate neuronal COX-2 expression and activity. We show that synaptic NMDARs enhance neuronal COX-2 expression, while sustained synaptic stimulation limits COX-2 activity by suppressing cellular levels of the primary COX-2 substrate, arachidonic acid (AA). In contrast, extrasynaptic NMDARs suppress COX-2 expression while activating phospholipase A2 (PLA2), which enhances AA levels by hydrolysis of membrane phospholipids. Thus, sequential activation of synaptic then extrasynaptic NMDARs maximizes COX-2-dependent prostaglandin synthesis. We also show that excitotoxic events only drive induction of COX-2 expression through abnormal synaptic network excitability. Finally, we show that non-enzymatic lipid peroxidation of arachidonic and other polyunsaturated fatty acids is a function of network activity history. A new paradigm emerges from our results suggesting that pathological COX-2 signaling associated with models of stroke, epilepsy, and neurodegeneration requires specific spatio-temporal NMDAR stimulation. PMID:21957234
Population death sequences and Cox processes driven by interacting Feller diffusions
NASA Astrophysics Data System (ADS)
Wei, Gang; Clifford, Peter; Feng, Jianfeng
2002-11-01
We carry out a complete study on the relationship between Cox processes driven by interacting Feller diffusions and death sequences of immigration-emigration linked population networks. It is first proved that the Cox process driven by a Feller diffusion is equivalent to the death sequence of a birth and death process. The conclusion is then generalized to the case of Cox processes driven by interacting Feller diffusions and death sequences of interacting populations.
Probiotics regulate the expression of COX-2 in intestinal epithelial cells.
Otte, Jan-Michel; Mahjurian-Namari, Rudja; Brand, Stephan; Werner, Ilka; Schmidt, Wolfgang E; Schmitz, Frank
2009-01-01
Cyclooxygenase-2 (COX) 2 promotes intestinal wound healing but elicits also proinflammatory effects and has been implicated in colorectal carcinogenesis. Thus, a balanced expression of COX-2 is essential for intestinal homeostasis. This study was designed to evaluate the regulation of COX-2 by probiotic organisms and to characterize ligands and receptors involved. Colo320 and SW480 intestinal epithelial cells (IEC) were stimulated with gastrin or TNF-alpha and pre- or coincubated with commensales, bacterial supernatants, or distinct toll-like receptor (TLR) ligands. COX-2 promoter activity was determined by luciferase assays, protein expression by Western blotting, and secretion of prostaglandin E(2) (PGE(2)) by ELISA. Commensales differentially regulated COX-2 expression in IEC. E. coli Nissle 1917, the probiotic mixture VSL#3, and media conditioned by these organisms ameliorated induced COX-2 expression and PGE(2) secretion. Heat inactivation and DNase treatment significantly decreased these regulatory capacities. Lactobacillus acidophilus, however, significantly increased COX-2 expression and PGE(2) secretion. TLR agonists differentially ameliorated basal or induced COX-2 expression. Distinct probiotics specifically and significantly decrease induced COX-2 expression in IEC, most likely mediated by released factors and in part by bacterial DNA. A significant involvement of TLRs in these regulatory processes remains to be established. PMID:19116880
Molecular docking analysis of known flavonoids as duel COX-2 inhibitors in the context of cancer.
Dash, Raju; Uddin, Mir Muhammad Nasir; Hosen, S M Zahid; Rahim, Zahed Bin; Dinar, Abu Mansur; Kabir, Mohammad Shah Hafez; Sultan, Ramiz Ahmed; Islam, Ashekul; Hossain, Md Kamrul
2015-01-01
Cyclooxygenase-2 (COX-2) catalyzed synthesis of prostaglandin E2 and it associates with tumor growth, infiltration, and metastasis in preclinical experiments. Known inhibitors against COX-2 exhibit toxicity. Therefore, it is of interest to screen natural compounds like flavanoids against COX-2. Molecular docking using 12 known flavanoids against COX-2 by FlexX and of ArgusLab were performed. All compounds showed a favourable binding energy of >-10 KJ/mol in FlexX and > -8 kcal/mol in ArgusLab. However, this data requires in vitro and in vivo verification for further consideration. PMID:26770028
Molecular docking analysis of known flavonoids as duel COX-2 inhibitors in the context of cancer
Dash, Raju; Uddin, Mir Muhammad Nasir; Hosen, S.M. Zahid; Rahim, Zahed Bin; Dinar, Abu Mansur; Kabir, Mohammad Shah Hafez; Sultan, Ramiz Ahmed; Islam, Ashekul; Hossain, Md Kamrul
2015-01-01
Cyclooxygenase-2 (COX-2) catalyzed synthesis of prostaglandin E2 and it associates with tumor growth, infiltration, and metastasis in preclinical experiments. Known inhibitors against COX-2 exhibit toxicity. Therefore, it is of interest to screen natural compounds like flavanoids against COX-2. Molecular docking using 12 known flavanoids against COX-2 by FlexX and of ArgusLab were performed. All compounds showed a favourable binding energy of >-10 KJ/mol in FlexX and > -8 kcal/mol in ArgusLab. However, this data requires in vitro and in vivo verification for further consideration. PMID:26770028
Significance of Cox-2 expression in rectal cancers with or without preoperative radiotherapy
Pachkoria, Ketevan; Zhang Hong; Adell, Gunnar; Jarlsfelt, Ingvar; Sun Xiaofeng . E-mail: xiao-feng.sun@ibk.liu.se
2005-11-01
Purpose: Radiotherapy has reduced local recurrence of rectal cancers, but the result is not satisfactory. Further biologic factors are needed to identify patients for more effective radiotherapy. Our aims were to investigate the relationship of cyclooxygenase-2 (Cox-2) expression to radiotherapy, and clinicopathologic/biologic variables in rectal cancers with or without radiotherapy. Methods and Materials: Cox-2 expression was immunohistochemically examined in distal normal mucosa (n = 28), in adjacent normal mucosa (n = 107), in primary cancer (n = 138), lymph node metastasis (n = 30), and biopsy (n = 85). The patients participated in a rectal cancer trial of preoperative radiotherapy. Results: Cox-2 expression was increased in primary tumor compared with normal mucosa (p < 0.0001), but there was no significant change between primary tumor and metastasis. Cox-2 positivity was or tended to be related to more p53 and Ki-67 expression, and less apoptosis (p {<=} 0.05). In Cox-2-negative cases of either biopsy (p = 0.01) or surgical samples (p = 0.02), radiotherapy was related to less frequency of local recurrence, but this was not the case in Cox-2-positive cases. Conclusion: Cox-2 expression seemed to be an early event involved in rectal cancer development. Radiotherapy might reduce a rate of local recurrence in the patients with Cox-2 weakly stained tumors, but not in those with Cox-2 strongly stained tumors.
Selective COX-2 Inhibitors: A Review of Their Structure-Activity Relationships
Zarghi, Afshin; Arfaei, Sara
2011-01-01
Non-steroidal anti-inflammatory drugs (NSAIDs) are the competitive inhibitors of cyclooxygenase (COX), the enzyme which mediates the bioconversion of arachidonic acid to inflammatory prostaglandins (PGs). Their use is associated with the side effects such as gastrointestinal and renal toxicity. The therapeutic anti-inflammatory action of NSAIDs is produced by the inhibition of COX-2, while the undesired side effects arise from inhibition of COX-1 activity. Thus, it was though that more selective COX-2 inhibitors would have reduced side effects. Based upon a number of selective COX-2 inhibitors (rofecoxib, celecoxib, valdecoxibetc.) were developed as safer NSAIDs with improved gastric safety profile. However, the recent market removal of some COXIBs such as rofecoxib due to its adverse cardiovascular side effects clearly encourages the researchers to explore and evaluate alternative templates with COX-2 inhibitory activity. Recognition of new avenues for selective COX-2 inhibitors in cancer chemotherapy and neurological diseases such as Parkinson and Alzheimer’s diseases still continues to attract investigations on the development of COX-2 inhibitors. This review highlights the various structural classes of selective COX-2 inhibitors with special emphasis on their structure-activity relationships. PMID:24250402
Urinary arsenic concentration adjustment factors and malnutrition.
Nermell, Barbro; Lindberg, Anna-Lena; Rahman, Mahfuzar; Berglund, Marika; Persson, Lars Ake; El Arifeen, Shams; Vahter, Marie
2008-02-01
This study aims at evaluating the suitability of adjusting urinary concentrations of arsenic, or any other urinary biomarker, for variations in urine dilution by creatinine and specific gravity in a malnourished population. We measured the concentrations of metabolites of inorganic arsenic, creatinine and specific gravity in spot urine samples collected from 1466 individuals, 5-88 years of age, in Matlab, rural Bangladesh, where arsenic-contaminated drinking water and malnutrition are prevalent (about 30% of the adults had body mass index (BMI) below 18.5 kg/m(2)). The urinary concentrations of creatinine were low; on average 0.55 g/L in the adolescents and adults and about 0.35 g/L in the 5-12 years old children. Therefore, adjustment by creatinine gave much higher numerical values for the urinary arsenic concentrations than did the corresponding data expressed as microg/L, adjusted by specific gravity. As evaluated by multiple regression analyses, urinary creatinine, adjusted by specific gravity, was more affected by body size, age, gender and season than was specific gravity. Furthermore, urinary creatinine was found to be significantly associated with urinary arsenic, which further disqualifies the creatinine adjustment. PMID:17900556
Interpretation of Standardized Regression Coefficients in Multiple Regression.
ERIC Educational Resources Information Center
Thayer, Jerome D.
The extent to which standardized regression coefficients (beta values) can be used to determine the importance of a variable in an equation was explored. The beta value and the part correlation coefficient--also called the semi-partial correlation coefficient and reported in squared form as the incremental "r squared"--were compared for variables…
Demosaicing Based on Directional Difference Regression and Efficient Regression Priors.
Wu, Jiqing; Timofte, Radu; Van Gool, Luc
2016-08-01
Color demosaicing is a key image processing step aiming to reconstruct the missing pixels from a recorded raw image. On the one hand, numerous interpolation methods focusing on spatial-spectral correlations have been proved very efficient, whereas they yield a poor image quality and strong visible artifacts. On the other hand, optimization strategies, such as learned simultaneous sparse coding and sparsity and adaptive principal component analysis-based algorithms, were shown to greatly improve image quality compared with that delivered by interpolation methods, but unfortunately are computationally heavy. In this paper, we propose efficient regression priors as a novel, fast post-processing algorithm that learns the regression priors offline from training data. We also propose an independent efficient demosaicing algorithm based on directional difference regression, and introduce its enhanced version based on fused regression. We achieve an image quality comparable to that of the state-of-the-art methods for three benchmarks, while being order(s) of magnitude faster. PMID:27254866
Yang, Man; Wang, Hong-Tao; Zhao, Miao; Meng, Wen-Bo; Ou, Jin-Qing; He, Jun-Hui; Zou, Bing; Lei, Ping-Guang
2015-01-01
Abstract Currently 2 difference classes of cyclooxygenase (COX)-2 inhibitors, coxibs and relatively selective COX-2 inhibitors, are available for patients requiring nonsteroidal anti-inflammatory drug (NSAID) therapy; their gastroprotective effect is hardly directly compared. The aim of this study was to compare the gastroprotective effect of relatively selective COX-2 inhibitors with coxibs. MEDLINE, EMBASE, and the Cochrane Library (from their inception to March 2015) were searched for potential eligible studies. We included randomized controlled trials comparing coxibs (celecoxib, etoricoxib, parecoxib, and lumiracoxib), relatively selective COX-2 inhibitors (nabumetone, meloxicam, and etodolac), and nonselective NSAIDs with a study duration ≥4 weeks. Comparative effectiveness and safety data were pooled by Bayesian network meta-analysis. The primary outcomes were ulcer complications and symptomatic ulcer. Summary effect-size was calculated as risk ratio (RR), together with the 95% confidence interval (CI). This study included 36 trials with a total of 112,351 participants. Network meta-analyses indicated no significant difference between relatively selective COX-2 inhibitors and coxibs regarding ulcer complications (RR, 1.38; 95% CI, 0.47–3.27), symptomatic ulcer (RR, 1.02; 95% CI, 0.09–3.92), and endoscopic ulcer (RR, 1.18; 95% CI, 0.37–2.96). Network meta-analyses adjusting potential influential factors (age, sex, previous ulcer disease, and follow-up time), and sensitivity analyses did not reveal any major change to the main results. Network meta-analyses suggested that relatively selective COX-2 inhibitors and coxibs were associated with comparable incidences of total adverse events (AEs) (RR, 1.09; 95% CI, 0.93–1.31), gastrointestinal AEs (RR, 1.04; 95% CI, 0.87–1.25), total withdrawals (RR, 1.00; 95% CI, 0.74–1.33), and gastrointestinal AE-related withdrawals (RR, 1.02; 95% CI, 0.57–1.74). Relatively selective COX-2 inhibitors appear to be
Yang, Man; Wang, Hong-Tao; Zhao, Miao; Meng, Wen-Bo; Ou, Jin-Qing; He, Jun-Hui; Zou, Bing; Lei, Ping-Guang
2015-10-01
Currently 2 difference classes of cyclooxygenase (COX)-2 inhibitors, coxibs and relatively selective COX-2 inhibitors, are available for patients requiring nonsteroidal anti-inflammatory drug (NSAID) therapy; their gastroprotective effect is hardly directly compared. The aim of this study was to compare the gastroprotective effect of relatively selective COX-2 inhibitors with coxibs. MEDLINE, EMBASE, and the Cochrane Library (from their inception to March 2015) were searched for potential eligible studies. We included randomized controlled trials comparing coxibs (celecoxib, etoricoxib, parecoxib, and lumiracoxib), relatively selective COX-2 inhibitors (nabumetone, meloxicam, and etodolac), and nonselective NSAIDs with a study duration ≥ 4 weeks. Comparative effectiveness and safety data were pooled by Bayesian network meta-analysis. The primary outcomes were ulcer complications and symptomatic ulcer. Summary effect-size was calculated as risk ratio (RR), together with the 95% confidence interval (CI). This study included 36 trials with a total of 112,351 participants. Network meta-analyses indicated no significant difference between relatively selective COX-2 inhibitors and coxibs regarding ulcer complications (RR, 1.38; 95% CI, 0.47-3.27), symptomatic ulcer (RR, 1.02; 95% CI, 0.09-3.92), and endoscopic ulcer (RR, 1.18; 95% CI, 0.37-2.96). Network meta-analyses adjusting potential influential factors (age, sex, previous ulcer disease, and follow-up time), and sensitivity analyses did not reveal any major change to the main results. Network meta-analyses suggested that relatively selective COX-2 inhibitors and coxibs were associated with comparable incidences of total adverse events (AEs) (RR, 1.09; 95% CI, 0.93-1.31), gastrointestinal AEs (RR, 1.04; 95% CI, 0.87-1.25), total withdrawals (RR, 1.00; 95% CI, 0.74-1.33), and gastrointestinal AE-related withdrawals (RR, 1.02; 95% CI, 0.57-1.74). Relatively selective COX-2 inhibitors appear to be associated with
Interquantile Shrinkage in Regression Models
Jiang, Liewen; Wang, Huixia Judy; Bondell, Howard D.
2012-01-01
Conventional analysis using quantile regression typically focuses on fitting the regression model at different quantiles separately. However, in situations where the quantile coefficients share some common feature, joint modeling of multiple quantiles to accommodate the commonality often leads to more efficient estimation. One example of common features is that a predictor may have a constant effect over one region of quantile levels but varying effects in other regions. To automatically perform estimation and detection of the interquantile commonality, we develop two penalization methods. When the quantile slope coefficients indeed do not change across quantile levels, the proposed methods will shrink the slopes towards constant and thus improve the estimation efficiency. We establish the oracle properties of the two proposed penalization methods. Through numerical investigations, we demonstrate that the proposed methods lead to estimations with competitive or higher efficiency than the standard quantile regression estimation in finite samples. Supplemental materials for the article are available online. PMID:24363546