844 resultados para hidden Markov chains
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BACKGROUND: Low-molecular-weight heparin (LMWH) appears to be safe and effective for treating pulmonary embolism (PE), but its cost-effectiveness has not been assessed. METHODS: We built a Markov state-transition model to evaluate the medical and economic outcomes of a 6-day course with fixed-dose LMWH or adjusted-dose unfractionated heparin (UFH) in a hypothetical cohort of 60-year-old patients with acute submassive PE. Probabilities for clinical outcomes were obtained from a meta-analysis of clinical trials. Cost estimates were derived from Medicare reimbursement data and other sources. The base-case analysis used an inpatient setting, whereas secondary analyses examined early discharge and outpatient treatment with LMWH. Using a societal perspective, strategies were compared based on lifetime costs, quality-adjusted life-years (QALYs), and the incremental cost-effectiveness ratio. RESULTS: Inpatient treatment costs were higher for LMWH treatment than for UFH (dollar 13,001 vs dollar 12,780), but LMWH yielded a greater number of QALYs than did UFH (7.677 QALYs vs 7.493 QALYs). The incremental costs of dollar 221 and the corresponding incremental effectiveness of 0.184 QALYs resulted in an incremental cost-effectiveness ratio of dollar 1,209/QALY. Our results were highly robust in sensitivity analyses. LMWH became cost-saving if the daily pharmacy costs for LMWH were < dollar 51, if > or = 8% of patients were eligible for early discharge, or if > or = 5% of patients could be treated entirely as outpatients. CONCLUSION: For inpatient treatment of PE, the use of LMWH is cost-effective compared to UFH. Early discharge or outpatient treatment in suitable patients with PE would lead to substantial cost savings.
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In a weighted spatial network, as specified by an exchange matrix, the variances of the spatial values are inversely proportional to the size of the regions. Spatial values are no more exchangeable under independence, thus weakening the rationale for ordinary permutation and bootstrap tests of spatial autocorrelation. We propose an alternative permutation test for spatial autocorrelation, based upon exchangeable spatial modes, constructed as linear orthogonal combinations of spatial values. The coefficients obtain as eigenvectors of the standardised exchange matrix appearing in spectral clustering, and generalise to the weighted case the concept of spatial filtering for connectivity matrices. Also, two proposals aimed at transforming an acessibility matrix into a exchange matrix with with a priori fixed margins are presented. Two examples (inter-regional migratory flows and binary adjacency networks) illustrate the formalism, rooted in the theory of spectral decomposition for reversible Markov chains.
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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: Cleavage of messenger RNA (mRNA) precursors is an essential step in mRNA maturation. The signal recognized by the cleavage enzyme complex has been characterized as an A rich region upstream of the cleavage site containing a motif with consensus AAUAAA, followed by a U or UG rich region downstream of the cleavage site. RESULTS: We studied these signals using exhaustive databases of cleavage sites obtained from aligning raw expressed sequence tags (EST) sequences to genomic sequences in Homo sapiens and Drosophila melanogaster. These data show that the polyadenylation signal is highly conserved in human and fly. In addition, de novo motif searches generated a refined description of the U-rich downstream sequence (DSE) element, which shows more divergence between the two species. These refined motifs are applied, within a Hidden Markov Model (HMM) framework, to predict mRNA cleavage sites. CONCLUSION: We demonstrate that the DSE is a specific motif in both human and Drosophila. These findings shed light on the sequence correlates of a highly conserved biological process, and improve in silico prediction of 3' mRNA cleavage and polyadenylation sites.
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The ability to determine the location and relative strength of all transcription-factor binding sites in a genome is important both for a comprehensive understanding of gene regulation and for effective promoter engineering in biotechnological applications. Here we present a bioinformatically driven experimental method to accurately define the DNA-binding sequence specificity of transcription factors. A generalized profile was used as a predictive quantitative model for binding sites, and its parameters were estimated from in vitro-selected ligands using standard hidden Markov model training algorithms. Computer simulations showed that several thousand low- to medium-affinity sequences are required to generate a profile of desired accuracy. To produce data on this scale, we applied high-throughput genomics methods to the biochemical problem addressed here. A method combining systematic evolution of ligands by exponential enrichment (SELEX) and serial analysis of gene expression (SAGE) protocols was coupled to an automated quality-controlled sequence extraction procedure based on Phred quality scores. This allowed the sequencing of a database of more than 10,000 potential DNA ligands for the CTF/NFI transcription factor. The resulting binding-site model defines the sequence specificity of this protein with a high degree of accuracy not achieved earlier and thereby makes it possible to identify previously unknown regulatory sequences in genomic DNA. A covariance analysis of the selected sites revealed non-independent base preferences at different nucleotide positions, providing insight into the binding mechanism.
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BACKGROUND: Physician training in smoking cessation counseling has been shown to be effective as a means to increase quit success. We assessed the cost-effectiveness ratio of a smoking cessation counseling training programme. Its effectiveness was previously demonstrated in a cluster randomized, control trial performed in two Swiss university outpatients clinics, in which residents were randomized to receive training in smoking interventions or a control educational intervention. DESIGN AND METHODS: We used a Markov simulation model for effectiveness analysis. This model incorporates the intervention efficacy, the natural quit rate, and the lifetime probability of relapse after 1-year abstinence. We used previously published results in addition to hospital service and outpatient clinic cost data. The time horizon was 1 year, and we opted for a third-party payer perspective. RESULTS: The incremental cost of the intervention amounted to US$2.58 per consultation by a smoker, translating into a cost per life-year saved of US$25.4 for men and 35.2 for women. One-way sensitivity analyses yielded a range of US$4.0-107.1 in men and US$9.7-148.6 in women. Variations in the quit rate of the control intervention, the length of training effectiveness, and the discount rate yielded moderately large effects on the outcome. Variations in the natural cessation rate, the lifetime probability of relapse, the cost of physician training, the counseling time, the cost per hour of physician time, and the cost of the booklets had little effect on the cost-effectiveness ratio. CONCLUSIONS: Training residents in smoking cessation counseling is a very cost-effective intervention and may be more efficient than currently accepted tobacco control interventions.
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We present MBIS (Multivariate Bayesian Image Segmentation tool), a clustering tool based on the mixture of multivariate normal distributions model. MBIS supports multichannel bias field correction based on a B-spline model. A second methodological novelty is the inclusion of graph-cuts optimization for the stationary anisotropic hidden Markov random field model. Along with MBIS, we release an evaluation framework that contains three different experiments on multi-site data. We first validate the accuracy of segmentation and the estimated bias field for each channel. MBIS outperforms a widely used segmentation tool in a cross-comparison evaluation. The second experiment demonstrates the robustness of results on atlas-free segmentation of two image sets from scan-rescan protocols on 21 healthy subjects. Multivariate segmentation is more replicable than the monospectral counterpart on T1-weighted images. Finally, we provide a third experiment to illustrate how MBIS can be used in a large-scale study of tissue volume change with increasing age in 584 healthy subjects. This last result is meaningful as multivariate segmentation performs robustly without the need for prior knowledge.
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Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.
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OBJECTIVE: To examine the incremental cost effectiveness of the five first line pharmacological smoking cessation therapies in the Seychelles and other developing countries. DESIGN: A Markov chain cohort simulation. SUBJECTS: Two simulated cohorts of smokers: (1) a reference cohort given physician counselling only; (2) a treatment cohort given counselling plus cessation therapy. INTERVENTION: Addition of each of the five pharmacological cessation therapies to physician provided smoking cessation counselling. MAIN OUTCOME MEASURES: Cost per life-year saved (LYS) associated with the five pharmacotherapies. Effectiveness expressed as odds ratios for quitting associated with pharmacotherapies. Costs based on the additional physician time required and retail prices of the medications. RESULTS: Based on prices for currently available generic medications on the global market, the incremental cost per LYS for a 45 year old in the Seychelles was 599 US dollars for gum and 227 dollars for bupropion. Assuming US treatment prices as a conservative estimate, the incremental cost per LYS was significantly higher, though still favourable in comparison to other common medical interventions: 3712 dollars for nicotine gum, 1982 dollars for nicotine patch, 4597 dollars for nicotine spray, 4291 dollars for nicotine inhaler, and 1324 dollars for bupropion. Cost per LYS increased significantly upon application of higher discount rates, which may be used to reflect relatively high opportunity costs for health expenditures in developing countries with highly constrained resources and high overall mortality. CONCLUSION: Pharmacological cessation therapy can be highly cost effective as compared to other common medical interventions in low mortality, middle income countries, particularly if medications can be procured at low prices.
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PURPOSE: To predict the risk of an adolescent patient to miss an appointment, based on the previous appointments and on the characteristics of the patient and the appointment. METHODS: Two thousand one hundred ninety-three (1873 females) patients aged 12 to 20 years having scheduled at least four appointments were included. We assessed the rate of missed nonexcused appointments of each patient. Second, a Markovian multilevel model was used to predict the risk of defaulting. RESULTS: Forty-five percent of the patients have not missed even once, and 14% of females and 17% of males have missed >25% of their appointments. Females show two types of behaviors (an abstract concept that groups individuals based on a combination of their appointment-keeping and their recorded type of healthcare need) depending on the diagnosis. Somatic, gynecology, violence, and counseling diagnoses are mostly grouped together. In this group, having already missed and having an appointment with a paramedical provider increases the risk of missing. In the second group (eating disorders and psychiatric diagnoses) having already missed and a longer delay between appointments influence the risk of missing, although the risk is lower for this latter group. Males only show one type of behavior regarding missed appointments. Having missed a previous appointment, being older, having cancelled the next to last appointment and the type of diagnosis explain the risk of missing. CONCLUSIONS: Patients who have already defaulted have a higher risk of defaulting again. Means of control regarding missed appointments should consequently focus on defaulters, to decrease the associated workload. Reminders could be a solution for the follow-up appointments scheduled with a long delay.
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We propose a deep study on tissue modelization andclassification Techniques on T1-weighted MR images. Threeapproaches have been taken into account to perform thisvalidation study. Two of them are based on FiniteGaussian Mixture (FGM) model. The first one consists onlyin pure gaussian distributions (FGM-EM). The second oneuses a different model for partial volume (PV) (FGM-GA).The third one is based on a Hidden Markov Random Field(HMRF) model. All methods have been tested on a DigitalBrain Phantom image considered as the ground truth. Noiseand intensity non-uniformities have been added tosimulate real image conditions. Also the effect of ananisotropic filter is considered. Results demonstratethat methods relying in both intensity and spatialinformation are in general more robust to noise andinhomogeneities. However, in some cases there is nosignificant differences between all presented methods.
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Abstract One of the most important issues in molecular biology is to understand regulatory mechanisms that control gene expression. Gene expression is often regulated by proteins, called transcription factors which bind to short (5 to 20 base pairs),degenerate segments of DNA. Experimental efforts towards understanding the sequence specificity of transcription factors is laborious and expensive, but can be substantially accelerated with the use of computational predictions. This thesis describes the use of algorithms and resources for transcriptionfactor binding site analysis in addressing quantitative modelling, where probabilitic models are built to represent binding properties of a transcription factor and can be used to find new functional binding sites in genomes. Initially, an open-access database(HTPSELEX) was created, holding high quality binding sequences for two eukaryotic families of transcription factors namely CTF/NF1 and LEFT/TCF. The binding sequences were elucidated using a recently described experimental procedure called HTP-SELEX, that allows generation of large number (> 1000) of binding sites using mass sequencing technology. For each HTP-SELEX experiments we also provide accurate primary experimental information about the protein material used, details of the wet lab protocol, an archive of sequencing trace files, and assembled clone sequences of binding sequences. The database also offers reasonably large SELEX libraries obtained with conventional low-throughput protocols.The database is available at http://wwwisrec.isb-sib.ch/htpselex/ and and ftp://ftp.isrec.isb-sib.ch/pub/databases/htpselex. The Expectation-Maximisation(EM) algorithm is one the frequently used methods to estimate probabilistic models to represent the sequence specificity of transcription factors. We present computer simulations in order to estimate the precision of EM estimated models as a function of data set parameters(like length of initial sequences, number of initial sequences, percentage of nonbinding sequences). We observed a remarkable robustness of the EM algorithm with regard to length of training sequences and the degree of contamination. The HTPSELEX database and the benchmarked results of the EM algorithm formed part of the foundation for the subsequent project, where a statistical framework called hidden Markov model has been developed to represent sequence specificity of the transcription factors CTF/NF1 and LEF1/TCF using the HTP-SELEX experiment data. The hidden Markov model framework is capable of both predicting and classifying CTF/NF1 and LEF1/TCF binding sites. A covariance analysis of the binding sites revealed non-independent base preferences at different nucleotide positions, providing insight into the binding mechanism. We next tested the LEF1/TCF model by computing binding scores for a set of LEF1/TCF binding sequences for which relative affinities were determined experimentally using non-linear regression. The predicted and experimentally determined binding affinities were in good correlation.
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A variety of cellular proteins has the ability to recognize DNA lesions induced by the anti-cancer drug cisplatin, with diverse consequences on their repair and on the therapeutic effectiveness of this drug. We report a novel gene involved in the cell response to cisplatin in vertebrates. The RDM1 gene (for RAD52 Motif 1) was identified while searching databases for sequences showing similarities to RAD52, a protein involved in homologous recombination and DNA double-strand break repair. Ablation of RDM1 in the chicken B cell line DT40 led to a more than 3-fold increase in sensitivity to cisplatin. However, RDM1-/- cells were not hypersensitive to DNA damages caused by ionizing radiation, UV irradiation, or the alkylating agent methylmethane sulfonate. The RDM1 protein displays a nucleic acid binding domain of the RNA recognition motif (RRM) type. By using gel-shift assays and electron microscopy, we show that purified, recombinant chicken RDM1 protein interacts with single-stranded DNA as well as double-stranded DNA, on which it assembles filament-like structures. Notably, RDM1 recognizes DNA distortions induced by cisplatin-DNA adducts in vitro. Finally, human RDM1 transcripts are abundant in the testis, suggesting a possible role during spermatogenesis.
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Ocean currents, prevailing winds, and the hierarchical structures of river networks are known to create asymmetries in re-colonization between habitat patches. The impacts of such asymmetries on metapopulation persistence are seldom considered, especially rarely in theoretical studies. Considering three classical models (the island, the stepping stone and the distance-dependent model), we explore how metapopulation persistence is affected by (i) asymmetry in dispersal strength, in which the colonization rate between two patches differs in direction, and (ii) asymmetry in connectivity, in which the overall colonization pattern displays asymmetry (circulating or dendritic networks). Viability can be drastically reduced when directional bias in dispersal strength is higher than 25%. Re-colonization patterns that allow for strong local connectivity provide the highest persistence compared to systems that allow circulation. Finally, asymmetry has relatively weak effects when metapopulations maintain strong general connectivity.