44 resultados para hierarchical hidden Markov model
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BACKGROUND: In vitro aggregating brain cell cultures containing all types of brain cells have been shown to be useful for neurotoxicological investigations. The cultures are used for the detection of nervous system-specific effects of compounds by measuring multiple endpoints, including changes in enzyme activities. Concentration-dependent neurotoxicity is determined at several time points. METHODS: A Markov model was set up to describe the dynamics of brain cell populations exposed to potentially neurotoxic compounds. Brain cells were assumed to be either in a healthy or stressed state, with only stressed cells being susceptible to cell death. Cells may have switched between these states or died with concentration-dependent transition rates. Since cell numbers were not directly measurable, intracellular lactate dehydrogenase (LDH) activity was used as a surrogate. Assuming that changes in cell numbers are proportional to changes in intracellular LDH activity, stochastic enzyme activity models were derived. Maximum likelihood and least squares regression techniques were applied for estimation of the transition rates. Likelihood ratio tests were performed to test hypotheses about the transition rates. Simulation studies were used to investigate the performance of the transition rate estimators and to analyze the error rates of the likelihood ratio tests. The stochastic time-concentration activity model was applied to intracellular LDH activity measurements after 7 and 14 days of continuous exposure to propofol. The model describes transitions from healthy to stressed cells and from stressed cells to death. RESULTS: The model predicted that propofol would affect stressed cells more than healthy cells. Increasing propofol concentration from 10 to 100 μM reduced the mean waiting time for transition to the stressed state by 50%, from 14 to 7 days, whereas the mean duration to cellular death reduced more dramatically from 2.7 days to 6.5 hours. CONCLUSION: The proposed stochastic modeling approach can be used to discriminate between different biological hypotheses regarding the effect of a compound on the transition rates. The effects of different compounds on the transition rate estimates can be quantitatively compared. Data can be extrapolated at late measurement time points to investigate whether costs and time-consuming long-term experiments could possibly be eliminated.
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BACKGROUND: Nicotine dependence is the major obstacle for smokers who want to quit. Guidelines have identified five effective first-line therapies, four nicotine replacement therapies (NRTs)--gum, patch, nasal spray and inhaler--and bupropion. Studying the extent to which these various treatments are cost-effective requires additional research. OBJECTIVES: To determine cost-effectiveness (CE) ratios of pharmacotherapies for nicotine dependence provided by general practitioners (GPs) during routine visits as an adjunct to cessation counselling. METHODS: We used a Markov model to generate two cohorts of one-pack-a-day smokers: (1) the reference cohort received only cessation counselling from a GP during routine office visits; (2) the second cohort received the same counselling plus an offer to use a pharmacological treatment to help them quit smoking. The effectiveness of adjunctive therapy was expressed in terms of the resultant differential in mortality rate between the two cohorts. Data on the effectiveness of therapies came from meta-analyses, and we used odds ratio for quitting as the measure of effectiveness. The costs of pharmacotherapies were based on the cost of the additional time spent by GPs offering, prescribing and following-up treatment, and on the retail prices of the therapies. We used the third-party-payer perspective. Results are expressed as the incremental cost per life-year saved. RESULTS: The cost per life-year saved for only counselling ranged from Euro 385 to Euro 622 for men and from Euro 468 to Euro 796 for women. The CE ratios for the five pharmacological treatments varied from Euro 1768 to Euro 6879 for men, and from Euro 2146 to Euro 8799 for women. Significant variations in CE ratios among the five treatments were primarily due to differences in retail prices. The most cost-effective treatments were bupropion and the patch, and, then, in descending order, the spray, the inhaler and, lastly, gum. Differences in CE between men and women across treatments were due to the shape of their respective mortality curve. The lowest CE ratio in men was for the 45- to 49-year-old group and for women in the 50- to 54-year-old group. Sensitivity analysis showed that changes in treatment efficacy produced effects only for less-well proven treatments (spray, inhaler, and bupropion) and revealed a strong influence of the discount rate and natural quit rate on the CE of pharmacological treatments. CONCLUSION: The CE of first-line treatments for nicotine dependence varied widely with age and sex and was sensitive to the assumption for the natural quit rate. Bupropion and the nicotine patch were the two most cost-effective treatments.
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BACKGROUND/AIMS: While several risk factors for the histological progression of chronic hepatitis C have been identified, the contribution of HCV genotypes to liver fibrosis evolution remains controversial. The aim of this study was to assess independent predictors for fibrosis progression. METHODS: We identified 1189 patients from the Swiss Hepatitis C Cohort database with at least one biopsy prior to antiviral treatment and assessable date of infection. Stage-constant fibrosis progression rate was assessed using the ratio of fibrosis Metavir score to duration of infection. Stage-specific fibrosis progression rates were obtained using a Markov model. Risk factors were assessed by univariate and multivariate regression models. RESULTS: Independent risk factors for accelerated stage-constant fibrosis progression (>0.083 fibrosis units/year) included male sex (OR=1.60, [95% CI 1.21-2.12], P<0.001), age at infection (OR=1.08, [1.06-1.09], P<0.001), histological activity (OR=2.03, [1.54-2.68], P<0.001) and genotype 3 (OR=1.89, [1.37-2.61], P<0.001). Slower progression rates were observed in patients infected by blood transfusion (P=0.02) and invasive procedures or needle stick (P=0.03), compared to those infected by intravenous drug use. Maximum likelihood estimates (95% CI) of stage-specific progression rates (fibrosis units/year) for genotype 3 versus the other genotypes were: F0-->F1: 0.126 (0.106-0.145) versus 0.091 (0.083-0.100), F1-->F2: 0.099 (0.080-0.117) versus 0.065 (0.058-0.073), F2-->F3: 0.077 (0.058-0.096) versus 0.068 (0.057-0.080) and F3-->F4: 0.171 (0.106-0.236) versus 0.112 (0.083-0.142, overall P<0.001). CONCLUSIONS: This study shows a significant association of genotype 3 with accelerated fibrosis using both stage-constant and stage-specific estimates of fibrosis progression rates. This observation may have important consequences for the management of patients infected with this genotype.
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BACKGROUND: Membrane-bound organelles are a defining feature of eukaryotic cells, and play a central role in most of their fundamental processes. The Rab G proteins are the single largest family of proteins that participate in the traffic between organelles, with 66 Rabs encoded in the human genome. Rabs direct the organelle-specific recruitment of vesicle tethering factors, motor proteins, and regulators of membrane traffic. Each organelle or vesicle class is typically associated with one or more Rab, with the Rabs present in a particular cell reflecting that cell's complement of organelles and trafficking routes. RESULTS: Through iterative use of hidden Markov models and tree building, we classified Rabs across the eukaryotic kingdom to provide the most comprehensive view of Rab evolution obtained to date. A strikingly large repertoire of at least 20 Rabs appears to have been present in the last eukaryotic common ancestor (LECA), consistent with the 'complexity early' view of eukaryotic evolution. We were able to place these Rabs into six supergroups, giving a deep view into eukaryotic prehistory. CONCLUSIONS: Tracing the fate of the LECA Rabs revealed extensive losses with many extant eukaryotes having fewer Rabs, and none having the full complement. We found that other Rabs have expanded and diversified, including a large expansion at the dawn of metazoans, which could be followed to provide an account of the evolutionary history of all human Rabs. Some Rab changes could be correlated with differences in cellular organization, and the relative lack of variation in other families of membrane-traffic proteins suggests that it is the changes in Rabs that primarily underlies the variation in organelles between species and cell types.
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The interpretation of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all crossloadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores.
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OBJECTIVES: To assess the incremental cost-effectiveness ratio (ICER) and incremental cost-utility ratio (ICUR) of risedronate compared to no intervention in postmenopausal osteoporotic women in a Swiss perspective. METHODS: A previously validated Markov model was populated with epidemiological and cost data specific to Switzerland and published utility values, and run on a population of 1,000 women of 70 years with established osteoporosis and previous vertebral fracture, treated over 5 years with risedronate 35 mg weekly or no intervention (base case), and five cohorts (according to age at therapy start) with eight risk factor distributions and three lengths of residual effects. RESULTS: In the base case population, the ICER of averting a hip fracture and the ICUR per quality-adjusted life year gained were both dominant. In the presence of a previous vertebral fracture, the ICUR was below euro45,000 (pound30,000) in all the scenarios. For all osteoporotic women>or=70 years of age with at least one risk factor, the ICUR was below euro45,000 or the intervention may even be cost saving. Age at the start of therapy and the fracture risk profile had a significant impact on results. CONCLUSION: Assuming a 2-year residual effect, that ICUR of risedronate in women with postmenopausal osteoporosis is below accepted thresholds from the age of 65 and even cost saving above the age of 70 with at least one risk factor.
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BACKGROUND: The obective of this study was to perform a cost-effectiveness analysis comparing intermittent with continuous renal replacement therapy (IRRT versus CRRT) as initial therapy for acute kidney injury (AKI) in the intensive care unit (ICU). METHODS: Assuming some patients would potentially be eligible for either modality, we modeled life year gained, the quality-adjusted life years (QALYs) and healthcare costs for a cohort of 1000 IRRT patients and a cohort of 1000 CRRT patients. We used a 1-year, 5-year and a lifetime horizon. A Markov model with two health states for AKI survivors was designed: dialysis dependence and dialysis independence. We applied Weibull regression from published estimates to fit survival curves for CRRT and IRRT patients and to fit the proportion of dialysis dependence among CRRT and IRRT survivors. We then applied a risk ratio reported in a large retrospective cohort study to the fitted CRRT estimates in order to determine the proportion of dialysis dependence for IRRT survivors. We conducted sensitivity analyses based on a range of differences for daily implementation cost between CRRT and IRRT (base case: CRRT day $632 more expensive than IRRT day; range from $200 to $1000) and a range of risk ratios for dialysis dependence for CRRT as compared with IRRT (from 0.65 to 0.95; base case: 0.80). RESULTS: Continuous renal replacement therapy was associated with a marginally greater gain in QALY as compared with IRRT (1.093 versus 1.078). Despite higher upfront costs for CRRT in the ICU ($4046 for CRRT versus $1423 for IRRT in average), the 5-year total cost including the cost of dialysis dependence was lower for CRRT ($37 780 for CRRT versus $39 448 for IRRT on average). The base case incremental cost-effectiveness analysis showed that CRRT dominated IRRT. This dominance was confirmed by extensive sensitivity analysis. CONCLUSIONS: Initial CRRT is cost-effective compared with initial IRRT by reducing the rate of long-term dialysis dependence among critically ill AKI survivors.
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OBJECTIVES:: For certain major operations, inpatient mortality risk is lower in high-volume hospitals than those in low-volume hospitals. Extending the analysis to a broader range of interventions and outcomes is necessary before adopting policies based on minimum volume thresholds. METHODS:: Using the United States 2004 Nationwide Inpatient Sample, we assessed the effect of intervention-specific and overall hospital volume on surgical complications, potentially avoidable reoperations, and deaths across 1.4 million interventions in 353 hospitals. Outcome variations across hospitals were analyzed through a 3-level hierarchical logistic regression model (patients, surgical interventions, and hospitals), which took into account interventions on multiple organs, 144 intervention categories, and structural hospital characteristics. Discriminative performance and calibration were good. RESULTS:: Hospitals with more experience in a given intervention had similar reoperation rates but lower mortality and complication rates: odds ratio per volume deciles 0.93 and 0.97. However, the benefit was limited to heart surgery and a small number of other operations. Risks were higher for hospitals that performed more interventions overall: odds ratio per 1000 for each event was approximately 1.02. Even after adjustment for specific volume, mortality varied substantially across both high- and low-volume hospitals. CONCLUSION:: Although the link between specific volume and certain inpatient outcomes suggests that specialization might help improve surgical safety, the variable magnitude of this link and the heterogeneity of hospital effect do not support the systematic use of volume-based referrals. It may be more efficient to monitor risk-adjusted postoperative outcomes and to investigate facilities with worse than expected outcomes.
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The current challenge in a context of major environmental changes is to anticipate the responses of species to future landscape and climate scenarios. In the Mediterranean basin, climate change is one the most powerful driving forces of fire dynamics, with fire frequency and impact having markedly increased in recent years. Species distribution modelling plays a fundamental role in this challenge, but better integration of available ecological knowledge is needed to adequately guide conservation efforts. Here, we quantified changes in habitat suitability of an early-succession bird in Catalonia, the Dartford Warbler (Sylvia undata) ― globally evaluated as Near Threatened in the IUCN Red List. We assessed potential changes in species distributions between 2000 and 2050 under different fire management and climate change scenarios and described landscape dynamics using a spatially-explicit fire-succession model that simulates fire impacts in the landscape and post-fire regeneration (MEDFIRE model). Dartford Warbler occurrence data were acquired at two different spatial scales from: 1) the Atlas of European Breeding Birds (EBCC) and 2) Catalan Breeding Bird Atlas (CBBA). Habitat suitability was modelled using five widely-used modelling techniques in an ensemble forecasting framework. Our results indicated considerable habitat suitability losses (ranging between 47% and 57% in baseline scenarios), which were modulated to a large extent by fire regime changes derived from fire management policies and climate changes. Such result highlighted the need for taking the spatial interaction between climate changes, fire-mediated landscape dynamics and fire management policies into account for coherently anticipating habitat suitability changes of early succession bird species. We conclude that fire management programs need to be integrated into conservation plans to effectively preserve sparsely forested and early succession habitats and their associated species in the face of global environmental change.
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Advances in flow cytometry and other single-cell technologies have enabled high-dimensional, high-throughput measurements of individual cells as well as the interrogation of cell population heterogeneity. However, in many instances, computational tools to analyze the wealth of data generated by these technologies are lacking. Here, we present a computational framework for unbiased combinatorial polyfunctionality analysis of antigen-specific T-cell subsets (COMPASS). COMPASS uses a Bayesian hierarchical framework to model all observed cell subsets and select those most likely to have antigen-specific responses. Cell-subset responses are quantified by posterior probabilities, and human subject-level responses are quantified by two summary statistics that describe the quality of an individual's polyfunctional response and can be correlated directly with clinical outcome. Using three clinical data sets of cytokine production, we demonstrate how COMPASS improves characterization of antigen-specific T cells and reveals cellular 'correlates of protection/immunity' in the RV144 HIV vaccine efficacy trial that are missed by other methods. COMPASS is available as open-source software.
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BACKGROUND: Available methods to simulate nucleotide or amino acid data typically use Markov models to simulate each position independently. These approaches are not appropriate to assess the performance of combinatorial and probabilistic methods that look for coevolving positions in nucleotide or amino acid sequences. RESULTS: We have developed a web-based platform that gives a user-friendly access to two phylogenetic-based methods implementing the Coev model: the evaluation of coevolving scores and the simulation of coevolving positions. We have also extended the capabilities of the Coev model to allow for the generalization of the alphabet used in the Markov model, which can now analyse both nucleotide and amino acid data sets. The simulation of coevolving positions is novel and builds upon the developments of the Coev model. It allows user to simulate pairs of dependent nucleotide or amino acid positions. CONCLUSIONS: The main focus of our paper is the new simulation method we present for coevolving positions. The implementation of this method is embedded within the web platform Coev-web that is freely accessible at http://coev.vital-it.ch/, and was tested in most modern web browsers.
The Mixture Transition Distribution Model for High-Order Markov Chains and Non-Gaussian Time Series.
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Probabilistic inversion methods based on Markov chain Monte Carlo (MCMC) simulation are well suited to quantify parameter and model uncertainty of nonlinear inverse problems. Yet, application of such methods to CPU-intensive forward models can be a daunting task, particularly if the parameter space is high dimensional. Here, we present a 2-D pixel-based MCMC inversion of plane-wave electromagnetic (EM) data. Using synthetic data, we investigate how model parameter uncertainty depends on model structure constraints using different norms of the likelihood function and the model constraints, and study the added benefits of joint inversion of EM and electrical resistivity tomography (ERT) data. Our results demonstrate that model structure constraints are necessary to stabilize the MCMC inversion results of a highly discretized model. These constraints decrease model parameter uncertainty and facilitate model interpretation. A drawback is that these constraints may lead to posterior distributions that do not fully include the true underlying model, because some of its features exhibit a low sensitivity to the EM data, and hence are difficult to resolve. This problem can be partly mitigated if the plane-wave EM data is augmented with ERT observations. The hierarchical Bayesian inverse formulation introduced and used herein is able to successfully recover the probabilistic properties of the measurement data errors and a model regularization weight. Application of the proposed inversion methodology to field data from an aquifer demonstrates that the posterior mean model realization is very similar to that derived from a deterministic inversion with similar model constraints.
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We consider a spectrally-negative Markov additive process as a model of a risk process in a random environment. Following recent interest in alternative ruin concepts, we assume that ruin occurs when an independent Poissonian observer sees the process as negative, where the observation rate may depend on the state of the environment. Using an approximation argument and spectral theory, we establish an explicit formula for the resulting survival probabilities in this general setting. We also discuss an efficient evaluation of the involved quantities and provide a numerical illustration.