On modifications to the long-term survival mixture model in the presence of competing risks

A mixture model for long-term survivors has been adopted in various fields such as biostatistics and criminology where some individuals may never experience the type of failure under study. It is directly applicable in situations where the only information available from follow-up on individuals who will never experience this type of failure is in the form of censored observations. In this paper, we consider a modification to the model so that it still applies in the case where during the follow-up period it becomes known that an individual will never experience failure from the cause of interest. Unless a model allows for this additional information, a consistent survival analysis will not be obtained. A partial maximum likelihood (ML) approach is proposed that preserves the simplicity of the long-term survival mixture model and provides consistent estimators of the quantities of interest. Some simulation experiments are performed to assess the efficiency of the partial ML approach relative to the full ML approach for survival in the presence of competing risks.

Robust Mixture Modelling Using the t Distribution

Normal mixture models are being increasingly used to model the distributions of a wide variety of random phenomena and to cluster sets of continuous multivariate data. However, for a set of data containing a group or groups of observations with longer than normal tails or atypical observations, the use of normal components may unduly affect the fit of the mixture model. In this paper, we consider a more robust approach by modelling the data by a mixture of t distributions. The use of the ECM algorithm to fit this t mixture model is described and examples of its use are given in the context of clustering multivariate data in the presence of atypical observations in the form of background noise.

Forward-looking versus recursive-dynamic modeling in climate policy analysis: A comparison

This paper develops a multi-regional general equilibrium model for climate policy analysis based on the latest version of the MIT Emissions Prediction and Policy Analysis (EPPA) model. We develop two versions so that we can solve the model either as a fully inter-temporal optimization problem (forward-looking, perfect foresight) or recursively. The standard EPPA model on which these models are based is solved recursively, and it is necessary to simplify some aspects of it to make inter-temporal solution possible. The forward-looking capability allows one to better address economic and policy issues such as borrowing and banking of GHG allowances, efficiency implications of environmental tax recycling, endogenous depletion of fossil resources, international capital flows, and optimal emissions abatement paths among others. To evaluate the solution approaches, we benchmark each version to the same macroeconomic path, and then compare the behavior of the two versions under a climate policy that restricts greenhouse gas emissions. We find that the energy sector and CO(2) price behavior are similar in both versions (in the recursive version of the model we force the inter-temporal theoretical efficiency result that abatement through time should be allocated such that the CO(2) price rises at the interest rate.) The main difference that arises is that the macroeconomic costs are substantially lower in the forward-looking version of the model, since it allows consumption shifting as an additional avenue of adjustment to the policy. On the other hand, the simplifications required for solving the model as an optimization problem, such as dropping the full vintaging of the capital stock and fewer explicit technological options, likely have effects on the results. Moreover, inter-temporal optimization with perfect foresight poorly represents the real economy where agents face high levels of uncertainty that likely lead to higher costs than if they knew the future with certainty. We conclude that while the forward-looking model has value for some problems, the recursive model produces similar behavior in the energy sector and provides greater flexibility in the details of the system that can be represented. (C) 2009 Elsevier B.V. All rights reserved.

Mucosal leishmaniasis: description of case management approaches and analysis of risk factors for treatment failure in a cohort of 140 patients in Brazil

Background Mucosal leishmaniasis is caused mainly by Leishmania braziliensis and it occurs months or years after cutaneous lesions. This progressive disease destroys cartilages and osseous structures from face, pharynx and larynx. Objective and methods The aim of this study was to analyse the significance of clinical and epidemiological findings, diagnosis and treatment with the outcome and recurrence of mucosal leishmaniasis through binary logistic regression model from 140 patients with mucosal leishmaniasis from a Brazilian centre. Results The median age of patients was 57.5 and systemic arterial hypertension was the most prevalent secondary disease found in patients with mucosal leishmaniasis (43%). Diabetes, chronic nephropathy and viral hepatitis, allergy and coagulopathy were found in less than 10% of patients. Human immunodeficiency virus (HIV) infection was found in 7 of 140 patients (5%). Rhinorrhea (47%) and epistaxis (75%) were the most common symptoms. N-methyl-glucamine showed a cure rate of 91% and recurrence of 22%. Pentamidine showed a similar rate of cure (91%) and recurrence (25%). Fifteen patients received itraconazole with a cure rate of 73% and recurrence of 18%. Amphotericin B was the drug used in 30 patients with 82% of response with a recurrence rate of 7%. The binary logistic regression analysis demonstrated that systemic arterial hypertension and HIV infection were associated with failure of the treatment (P < 0.05). Conclusion The current first-line mucosal leishmaniasis therapy shows an adequate cure but later recurrence. HIV infection and systemic arterial hypertension should be investigated before start the treatment of mucosal leishmaniasis. Conflicts of interest The authors are not part of any associations or commercial relationships that might represent conflicts of interest in the writing of this study (e.g. pharmaceutical stock ownership, consultancy, advisory board membership, relevant patents, or research funding).

miRNA analysis of prostate cancer by quantitative real time PCR: Comparison between formalin-fixed paraffin embedded and fresh-frozen tissue

Objective: Micro RNA (miRNA) is a class of small noncoding RNA that plays a major role in the regulation of gene expression, which has been related to cancer behavior. The possibility of analyzing miRNA from the archives of pathology laboratories is exciting, as it allows for large retrospective studies. Formalin is the most common fixative used in the surgical pathology routine, and its promotion of nucleic acid degradation is well known. Our aim is to compare miRNA profiles from formalin-fixed paraffin embedded (FFPE) tissues with fresh-frozen prostate cancer tissues. Methods: The expression of 14 miRNAs was determined by quantitative real time polymerase chain reaction (qRT-PCR) in 5 paired fresh-frozen and FFPE tissues, which were representative of prostate carcinoma. Results: There was a very good correlation of the miRNA expression of miR-let7c and miR-32 between the fresh-frozen and FFPE tissues, with Pearson`s correlation coefficients of 0.927 (P = 0.023) and 0.960 (P = 0.010), respectively. For the remaining miRNAs, the correlation was good with Spearman correlation coefficient of 0.638 (P < 0.001). Conclusion: Analysis of miRNAs from routinely processed and stored FFPE prostate tissue is feasible for some miRNAs using qRT-PCR. Further studies should be conducted to confirm the reliability of using stock tissues for miRNA expression determination. (C) 2011 Elsevier Inc. All rights reserved.

Detection of Auditory Cortex Activity by fMRI Using a Dependent Component Analysis

Functional MRI (fMRI) data often have low signal-to-noise-ratio (SNR) and are contaminated by strong interference from other physiological sources. A promising tool for extracting signals, even under low SNR conditions, is blind source separation (BSS), or independent component analysis (ICA). BSS is based on the assumption that the detected signals are a mixture of a number of independent source signals that are linearly combined via an unknown mixing matrix. BSS seeks to determine the mixing matrix to recover the source signals based on principles of statistical independence. In most cases, extraction of all sources is unnecessary; instead, a priori information can be applied to extract only the signal of interest. Herein we propose an algorithm based on a variation of ICA, called Dependent Component Analysis (DCA), where the signal of interest is extracted using a time delay obtained from an autocorrelation analysis. We applied such method to inspect functional Magnetic Resonance Imaging (fMRI) data, aiming to find the hemodynamic response that follows neuronal activation from an auditory stimulation, in human subjects. The method localized a significant signal modulation in cortical regions corresponding to the primary auditory cortex. The results obtained by DCA were also compared to those of the General Linear Model (GLM), which is the most widely used method to analyze fMRI datasets.

Stereoselective Analysis of Labetalol in Human Plasma by LC-MS/MS: Application to Pharmacokinetics

Labetalol is clinically available as a mixture of two racemates (four stereoisomers). The stereoisomer (R,R) has as main activity the beta(1)-antagonism and the stereoisomer (S,R) is highly selective for the alpha(1) adrenoceptor and is responsible for most of the alpha-blocker activity. In the present investigation, a method for the analysis of labetalol stereoisomers in human plasma was developed and applied to pharmacokinetic studies. Plasma samples (0.5 ml) were extracted with methyl tert-butyl ether at pH 9.5. The four labetalol stereoisomers were analyzed by LC-MS/MS on a Chirobiotic (R) V column using a mobile phase consisting of methanol, acetic acid, and diethylamine, with a recovery of more than 90% for all four. The quantitation limit was 0.5 ng/ml and linearity was observed at 250 ng/ml plasma for each stereoisomer. Studies of precision and accuracy presented coefficients of variation and percentage inaccuracy of less than 15%, indicating that the method is precise and accurate. The method was applied to the study of the kinetic disposition of labetalol over a period of 12 h after oral administration of a single 100 mg dose to a hypertensive pregnant woman. The clinical study revealed stereoselectivity in the pharmacokinetics of labetalol, with a lower plasma proportion for the active stereoisomers (R,R)-labetalol and (S,R)-labetalol. The stereoselectivity observed after oral administration is due to the hepatic metabolism and the first pass effect, with an AUC((R,R))/AUC((S,S)) ratio of 0.5. Chirality 21:738-744, 2009. (C) 2008 Wiley-Liss, Inc.

Socioeconomic causes of loss of animal genetic diversity: Analysis and assessment

The number of breeds of domesticated animals, especially livestock, have declined rapidly. The proximate causes and processes involved in loss of breeds are outlined. The path-dependent effect and Swanson's dominance-effect are discussed in relation to breed selection. While these help to explain genetic erosion, they need to be supplemented to provide a further explanation of biodiversity loss. It is shown that the extension of markets and economic globalisation have contributed significantly to genetic loss of breeds. In addition, the decoupling of animal husbandry from surrounding natural environmental conditions is further eroding the stock of genetic resources, particularly industrialised intensive animal husbandry. Recent trends in animal husbandry raise very serious sustainability issues, apart from animal welfare concerns.

Comparative analysis of root surface smear layer removal by different etching modalities or erbium:yttrium-aluminum-garnet laser irradiation. A scanning electron microscopy study

The purpose of this study was to evaluate the effect of erbium:yttrium-aluminum-garnet (Er:YAG) laser (2.94 mu m) irradiation on the removal of root surface smear layer of extracted human teeth and to compare its efficacy with that of citric acid, ethylenediamine tetra-acetic acid (EDTA), or a gel containing a mixture of tetracycline hydrochloride (HCl) and citric acid, using scanning electron microscopy (SEM). Thirty human dentin specimens were randomly divided into six groups: G1 (control group), irrigated with 10 ml of physiologic saline solution; G2, conditioned with 24% citric acid gel; G3, conditioned with 24% EDTA gel; G4, conditioned with a 50% citric acid and tetracycline gel; G5, irradiated with Er:YAG laser (47 mJ/10 Hz/5.8 J/cm(2)/pulse); G6, irradiated with Er:YAG laser (83 mJ/10 Hz/10.3 J/cm(2)/pulse). Electron micrographs were obtained and analyzed according to a rating system. Statistical analysis was conducted with Kruskal-Wallis and Mann-Whitney tests (P < 0.05). G1 was statistically different from all the other groups; no statistically significant differences were observed between the Er:YAG laser groups and those undergoing the other treatment modalities. When the two Er:YAG laser groups were compared, the fluency of G6 was statistically more effective in smear layer removal than the one used in G5 (Mann-Whitney test, P < 0.01). Root surfaces irradiated by Er:YAG laser had more irregular contours than those treated by chemical agents. It can be concluded that all treatment modalities were effective in smear layer removal. The results of our study suggest that the Er:YAG laser can be safely used to condition diseased root surfaces effectively. Furthermore, the effect of Er:YAG laser irradiation on root surfaces should be evaluated in vivo so that its potential to enhance the healing of periodontal tissues can be assessed.

Long-term survivor mixture model with random effects: application to a multi-centre clinical trial of carcinoma

A mixture model incorporating long-term survivors has been adopted in the field of biostatistics where some individuals may never experience the failure event under study. The surviving fractions may be considered as cured. In most applications, the survival times are assumed to be independent. However, when the survival data are obtained from a multi-centre clinical trial, it is conceived that the environ mental conditions and facilities shared within clinic affects the proportion cured as well as the failure risk for the uncured individuals. It necessitates a long-term survivor mixture model with random effects. In this paper, the long-term survivor mixture model is extended for the analysis of multivariate failure time data using the generalized linear mixed model (GLMM) approach. The proposed model is applied to analyse a numerical data set from a multi-centre clinical trial of carcinoma as an illustration. Some simulation experiments are performed to assess the applicability of the model based on the average biases of the estimates formed. Copyright (C) 2001 John Wiley & Sons, Ltd.

A longitudinal analysis of cytotoxic T lymphocyte precursor frequencies to the hepatitis B virus in chronically infected patients

Individuals with acute hepatitis B virus (HBV) infection characteristically mount a strong, multispecific cytotoxic T lymphocyte (CTL) response that is effective in eradicating virus. In contrast, this response in chronic carriers is usually weak or undetectable. Since it is generally acknowledged that HBV pathogenesis is immune-mediated, the occurrence of episodes of active liver disease in many carriers suggests that these individuals can mount active CTL responses to HBV. To see whether the detection of circulating CTLs is related to these flare episodes, we have determined the CTL precursor (CTLp) frequencies to HLA-A2-restricted viral peptides in seven patients over a 12-24-month period of their disease. Limiting dilution analyses (LDA) were performed longitudinally to five epitopes comprising the viral capsid (HBc), envelope (HBs) and polymerase (pol) proteins. Assays were performed against a mixture of peptides, or against each individual peptide, to measure overall CTL activity and the multispecificity of the responses, respectively. Since two of the patients were treated with recombinant human interleukin-12 (rHuIL-12) at the time, with one individual achieving complete disease remission a year later after being treated with interferon-alpha, we were also able to examine the effects of these cytokines on HBV cytotoxicity. Our results indicate that weak but detectable CTL responses do occur in chronic carriers which are generally associated with disease flares, although CTLps were also seen occasionally during minimal disease activity. The range of specificities varied between individuals and within each individual during the course of the disease. Finally, we also provide evidence that CTL reactivity is stimulated following treatment with certain cytokines, but is dependent on the time of administration.

Maximum Likelihood Estimation of Mixture Densities for Binned and Truncated Multivariate Data

Binning and truncation of data are common in data analysis and machine learning. This paper addresses the problem of fitting mixture densities to multivariate binned and truncated data. The EM approach proposed by McLachlan and Jones (Biometrics, 44: 2, 571-578, 1988) for the univariate case is generalized to multivariate measurements. The multivariate solution requires the evaluation of multidimensional integrals over each bin at each iteration of the EM procedure. Naive implementation of the procedure can lead to computationally inefficient results. To reduce the computational cost a number of straightforward numerical techniques are proposed. Results on simulated data indicate that the proposed methods can achieve significant computational gains with no loss in the accuracy of the final parameter estimates. Furthermore, experimental results suggest that with a sufficient number of bins and data points it is possible to estimate the true underlying density almost as well as if the data were not binned. The paper concludes with a brief description of an application of this approach to diagnosis of iron deficiency anemia, in the context of binned and truncated bivariate measurements of volume and hemoglobin concentration from an individual's red blood cells.

A mixture model-based approach to the clustering of microarray expression data

Motivation: This paper introduces the software EMMIX-GENE that has been developed for the specific purpose of a model-based approach to the clustering of microarray expression data, in particular, of tissue samples on a very large number of genes. The latter is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. A feasible approach is provided by first selecting a subset of the genes relevant for the clustering of the tissue samples by fitting mixtures of t distributions to rank the genes in order of increasing size of the likelihood ratio statistic for the test of one versus two components in the mixture model. The imposition of a threshold on the likelihood ratio statistic used in conjunction with a threshold on the size of a cluster allows the selection of a relevant set of genes. However, even this reduced set of genes will usually be too large for a normal mixture model to be fitted directly to the tissues, and so the use of mixtures of factor analyzers is exploited to reduce effectively the dimension of the feature space of genes. Results: The usefulness of the EMMIX-GENE approach for the clustering of tissue samples is demonstrated on two well-known data sets on colon and leukaemia tissues. For both data sets, relevant subsets of the genes are able to be selected that reveal interesting clusterings of the tissues that are either consistent with the external classification of the tissues or with background and biological knowledge of these sets.

Analysis of the microbial community structure and function of a laboratory scale enhanced biological phosphorus removal reactor

A laboratory scale sequencing batch reactor (SBR) operating for enhanced biological phosphorus removal (EBPR) and fed with a mixture of volatile fatty acids (VFAs) showed stable and efficient EBPR capacity over a four-year-period. Phosphorus (P), poly-beta-hydroxyalkanoate (PHA) and glycogen cycling consistent with classical anaerobic/aerobic EBPR were demonstrated with the order of anaerobic VFA uptake being propionate, acetate then butyrate. The SBR was operated without pH control and 63.67+/-13.86 mg P l(-1) was released anaerobically. The P% of the sludge fluctuated between 6% and 10% over the operating period (average of 8.04+/-1.31%). Four main morphological types of floc-forming bacteria were observed in the sludge during one year of in-tensive microscopic observation. Two of them were mainly responsible for anaerobic/aerobic P and PHA transformations. Fluorescence in situ hybridization (FISH) and post-FISH chemical staining for intracellular polyphosphate and PHA were used to determine that 'Candidatus Accumulibacter phosphatis' was the most abundant polyphosphate accumulating organism (PAO), forming large clusters of coccobacilli (1.0-1.5 mum) and comprising 53% of the sludge bacteria. Also by these methods, large coccobacillus-shaped gammaproteobacteria (2.5-3.5 mum) from a recently described novel cluster were glycogen-accumulating organisms (GAOs) comprising 13% of the bacteria. Tetrad-forming organisms (TFOs) consistent with the 'G bacterium' morphotype were alphaproteobacteria , but not Amaricoccus spp., and comprised 25% of all bacteria. According to chemical staining, TFOs were occasionally able to store PHA anaerobically and utilize it aerobically.

Stock discrimination and movements of narrow-barred Spanish mackerel across northern Australia as indicated by parasites

The parasite fauna of Spanish mackerel Scomberomorus commerson from 10 sites across northern Australia and one site in Indonesia, was examined to evaluate the degree of movement and subsequent stock structure of the fish. Kupang fish (Indonesia) had very few Terranova spp.. Grillotia branchi, Otobothrium cysticum or Pterobothrium sp. compared to Australian fish, indicating that no Australian fish enter the Kupang fishery. Univariate and discriminant function analysis of four 'temporary' parasite species, the copepod Pseudocyenoides armatus and the monogeneans Gotocotyla bivaginalis, Pricea multae and Pseudothoracocotyla ovalis, demonstrated little similarity between areas of northern Australia, indicating minimal short-term exchange between neighbouring groups of S. commerson. Analyses of five 'permanent' parasite species, the larval helminths G. branchi, O. cysticum, Pterobothrium sp., Callitetrarhynchus gracilis and Paranybelinia balli, also revealed large differences between areas thus indicating long-term separation. There are at least six parasitological stocks across northern Australia: Fog Bay/Bathurst Island, Cape Wessel. Groote/Sir Edward Pellew. Mornington Island, Weipa. and the Torres Strait. The occurrence of a few irregular fish in the samples suggested that LIP to 5% of fish moved between stocks during their lifetime. The similarity of within-school variability to that between schools showed that the fish do not form long-term school associations. (C) 2003 The Fisheries Society of the British Isles.