Discrete time Non-homogeneous Semi-Markov Processes applied to Models for Disability Insurance

In this paper, we present a stochastic model for disability insurance contracts. The model is based on a discrete time non-homogeneous semi-Markov process (DTNHSMP) to which the backward recurrence time process is introduced. This permits a more exhaustive study of disability evolution and a more efficient approach to the duration problem. The use of semi-Markov reward processes facilitates the possibility of deriving equations of the prospective and retrospective mathematical reserves. The model is applied to a sample of contracts drawn at random from a mutual insurance company.

Atomic force and electron microscopic-based study of sarcolemmal surface of living cardiomyocytes unveils unexpected mitochondrial shift in heart failure.

Loss of T-tubules (TT), sarcolemmal invaginations of cardiomyocytes (CMs), was recently identified as a general heart failure (HF) hallmark. However, whether TT per se or the overall sarcolemma is altered during HF process is still unknown. In this study, we directly examined sarcolemmal surface topography and physical properties using Atomic Force Microscopy (AFM) in living CMs from healthy and failing mice hearts. We confirmed the presence of highly organized crests and hollows along myofilaments in isolated healthy CMs. Sarcolemma topography was tightly correlated with elasticity, with crests stiffer than hollows and related to the presence of few packed subsarcolemmal mitochondria (SSM) as evidenced by electron microscopy. Three days after myocardial infarction (MI), CMs already exhibit an overall sarcolemma disorganization with general loss of crests topography thus becoming smooth and correlating with a decreased elasticity while interfibrillar mitochondria (IFM), myofilaments alignment and TT network were unaltered. End-stage post-ischemic condition (15days post-MI) exacerbates overall sarcolemma disorganization with, in addition to general loss of crest/hollow periodicity, a significant increase of cell surface stiffness. Strikingly, electron microscopy revealed the total depletion of SSM while some IFM heaps could be visualized beneath the membrane. Accordingly, mitochondrial Ca(2+) studies showed a heterogeneous pattern between SSM and IFM in healthy CMs which disappeared in HF. In vitro, formamide-induced sarcolemmal stress on healthy CMs phenocopied post-ischemic kinetics abnormalities and revealed initial SSM death and crest/hollow disorganization followed by IFM later disarray which moved toward the cell surface and structured heaps correlating with TT loss. This study demonstrates that the loss of crest/hollow organization of CM surface in HF occurs early and precedes disruption of the TT network. It also highlights a general stiffness increased of the CM surface most likely related to atypical IFM heaps while SSM died during HF process. Overall, these results indicate that initial sarcolemmal stress leading to SSM death could underlie subsequent TT disarray and HF setting.

MAMOT: hidden Markov modeling tool.

Hidden Markov models (HMMs) are probabilistic models that are well adapted to many tasks in bioinformatics, for example, for predicting the occurrence of specific motifs in biological sequences. MAMOT is a command-line program for Unix-like operating systems, including MacOS X, that we developed to allow scientists to apply HMMs more easily in their research. One can define the architecture and initial parameters of the model in a text file and then use MAMOT for parameter optimization on example data, decoding (like predicting motif occurrence in sequences) and the production of stochastic sequences generated according to the probabilistic model. Two examples for which models are provided are coiled-coil domains in protein sequences and protein binding sites in DNA. A wealth of useful features include the use of pseudocounts, state tying and fixing of selected parameters in learning, and the inclusion of prior probabilities in decoding. AVAILABILITY: MAMOT is implemented in C++, and is distributed under the GNU General Public Licence (GPL). The software, documentation, and example model files can be found at http://bcf.isb-sib.ch/mamot

The cost-effectiveness and public health benefit of nalmefene added to psychosocial support for the reduction of alcohol consumption in alcohol-dependent patients with high/very high drinking risk levels: a Markov model.

OBJECTIVES: To determine whether nalmefene combined with psychosocial support is cost-effective compared with psychosocial support alone for reducing alcohol consumption in alcohol-dependent patients with high/very high drinking risk levels (DRLs) as defined by the WHO, and to evaluate the public health benefit of reducing harmful alcohol-attributable diseases, injuries and deaths. DESIGN: Decision modelling using Markov chains compared costs and effects over 5 years. SETTING: The analysis was from the perspective of the National Health Service (NHS) in England and Wales. PARTICIPANTS: The model considered the licensed population for nalmefene, specifically adults with both alcohol dependence and high/very high DRLs, who do not require immediate detoxification and who continue to have high/very high DRLs after initial assessment. DATA SOURCES: We modelled treatment effect using data from three clinical trials for nalmefene (ESENSE 1 (NCT00811720), ESENSE 2 (NCT00812461) and SENSE (NCT00811941)). Baseline characteristics of the model population, treatment resource utilisation and utilities were from these trials. We estimated the number of alcohol-attributable events occurring at different levels of alcohol consumption based on published epidemiological risk-relation studies. Health-related costs were from UK sources. MAIN OUTCOME MEASURES: We measured incremental cost per quality-adjusted life year (QALY) gained and number of alcohol-attributable harmful events avoided. RESULTS: Nalmefene in combination with psychosocial support had an incremental cost-effectiveness ratio (ICER) of £5204 per QALY gained, and was therefore cost-effective at the £20,000 per QALY gained decision threshold. Sensitivity analyses showed that the conclusion was robust. Nalmefene plus psychosocial support led to the avoidance of 7179 alcohol-attributable diseases/injuries and 309 deaths per 100,000 patients compared to psychosocial support alone over the course of 5 years. CONCLUSIONS: Nalmefene can be seen as a cost-effective treatment for alcohol dependence, with substantial public health benefits. TRIAL REGISTRATION NUMBERS: This cost-effectiveness analysis was developed based on data from three randomised clinical trials: ESENSE 1 (NCT00811720), ESENSE 2 (NCT00812461) and SENSE (NCT00811941).

Does a shift in host plants trigger speciation in the Alpine leaf beetle Oreina speciosissima (Coleoptera, Chrysomelidae)?

Background: Within the Coleoptera, the largest order in the animal kingdom, the exclusively herbivorous Chrysomelidae are recognized as one of the most species rich beetle families. The evolutionary processes that have fueled radiation into the more than thirty-five thousand currently recognized leaf beetle species remain partly unresolved. The prominent role of leaf beetles in the insect world, their omnipresence across all terrestrial biomes and their economic importance as common agricultural pest organisms make this family particularly interesting for studying the mechanisms that drive diversification. Here we specifically focus on two ecotypes of the alpine leaf beetle Oreina speciosissima (Scop.), which have been shown to exhibit morphological differences in male genitalia roughly corresponding to the subspecies Oreina speciosissima sensu stricto and Oreina speciosissima troglodytes. In general the two ecotypes segregate along an elevation gradient and by host plants: Oreina speciosissima sensu stricto colonizes high forb vegetation at low altitude and Oreina speciosissima troglodytes is found in stone run vegetation at higher elevations. Both host plants and leaf beetles have a patchy geographical distribution. Through use of gene sequencing and genome fingerprinting (AFLP) we analyzed the genetic structure and habitat use of Oreina speciosissima populations from the Swiss Alps to examine whether the two ecotypes have a genetic basis. By investigating a wide range of altitudes and focusing on the structuring effect of habitat types, we aim to provide answers regarding the factors that drive adaptive radiation in this phytophagous leaf beetle.Results: While little phylogenetic resolution was observed based on the sequencing of four DNA regions, the topology and clustering resulting from AFLP genotyping grouped specimens according to their habitat, mostly defined by plant associations. A few specimens with intermediate morphologies clustered with one of the two ecotypes or formed separate clusters consistent with habitat differences. These results were discussed in an ecological speciation framework.Conclusions: The question of whether this case of ecological differentiation occurred in sympatry or allopatry remains open. Still, the observed pattern points towards ongoing divergence between the two ecotypes which is likely driven by a recent shift in host plant use.

The shift from low to high non-structural protein 1 expression in rotavirus-infected MA-104 cells

A hallmark of group/species A rotavirus (RVA) replication in MA-104 cells is the logarithmic increase in viral mRNAs that occurs four-12 h post-infection. Viral protein synthesis typically lags closely behind mRNA synthesis but continues after mRNA levels plateau. However, RVA non-structural protein 1 (NSP1) is present at very low levels throughout viral replication despite showing robust protein synthesis. NSP1 has the contrasting properties of being susceptible to proteasomal degradation, but being stabilised against proteasomal degradation by viral proteins and/or viral mRNAs. We aimed to determine the kinetics of the accumulation and intracellular distribution of NSP1 in MA-104 cells infected with rhesus rotavirus (RRV). NSP1 preferentially localises to the perinuclear region of the cytoplasm of infected cells, forming abundant granules that are heterogeneous in size. Late in infection, large NSP1 granules predominate, coincident with a shift from low to high NSP1 expression levels. Our results indicate that rotavirus NSP1 is a late viral protein in MA-104 cells infected with RRV, presumably as a result of altered protein turnover.

Mycobacteria mobility shift assay: a method for the rapid identification of Mycobacterium tuberculosis and nontuberculous mycobacteria

The identification of mycobacteria is essential because tuberculosis (TB) and mycobacteriosis are clinically indistinguishable and require different therapeutic regimens. The traditional phenotypic method is time consuming and may last up to 60 days. Indeed, rapid, affordable, specific and easy-to-perform identification methods are needed. We have previously described a polymerase chain reaction-based method called a mycobacteria mobility shift assay (MMSA) that was designed for Mycobacterium tuberculosis complex (MTC) and nontuberculous mycobacteria (NTM) species identification. The aim of this study was to assess the MMSA for the identification of MTC and NTM clinical isolates and to compare its performance with that of the PRA-hsp65 method. A total of 204 clinical isolates (102 NTM and 102 MTC) were identified by the MMSA and PRA-hsp65. For isolates for which these methods gave discordant results, definitive species identification was obtained by sequencing fragments of the 16S rRNA and hsp65 genes. Both methods correctly identified all MTC isolates. Among the NTM isolates, the MMSA alone assigned 94 (92.2%) to a complex or species, whereas the PRA-hsp65 method assigned 100% to a species. A 91.5% agreement was observed for the 94 NTM isolates identified by both methods. The MMSA provided correct identification for 96.8% of the NTM isolates compared with 94.7% for PRA-hsp65. The MMSA is a suitable auxiliary method for routine use for the rapid identification of mycobacteria.

Markov chain montecarlo method applied to rounding zeros of compositional data: first approach

As stated in Aitchison (1986), a proper study of relative variation in a compositional data set should be based on logratios, and dealing with logratios excludes dealing with zeros. Nevertheless, it is clear that zero observations might be present in real data sets, either because the corresponding part is completelyabsent –essential zeros– or because it is below detection limit –rounded zeros. Because the second kind of zeros is usually understood as “a trace too small to measure”, it seems reasonable to replace them by a suitable small value, and this has been the traditional approach. As stated, e.g. by Tauber (1999) and byMartín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2000), the principal problem in compositional data analysis is related to rounded zeros. One should be careful to use a replacement strategy that does not seriously distort the general structure of the data. In particular, the covariance structure of the involvedparts –and thus the metric properties– should be preserved, as otherwise further analysis on subpopulations could be misleading. Following this point of view, a non-parametric imputation method isintroduced in Martín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2000). This method is analyzed in depth by Martín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2003) where it is shown that thetheoretical drawbacks of the additive zero replacement method proposed in Aitchison (1986) can be overcome using a new multiplicative approach on the non-zero parts of a composition. The new approachhas reasonable properties from a compositional point of view. In particular, it is “natural” in the sense thatit recovers the “true” composition if replacement values are identical to the missing values, and it is coherent with the basic operations on the simplex. This coherence implies that the covariance structure of subcompositions with no zeros is preserved. As a generalization of the multiplicative replacement, in thesame paper a substitution method for missing values on compositional data sets is introduced

Bayesian Markov chain Monte Carlo inversion of geophysical data for the purpose of estimating the hydraulic properties of the unsaturated zone

Ground-penetrating radar (GPR) has the potential to provide valuable information on hydrological properties of the vadose zone because of their strong sensitivity to soil water content. In particular, recent evidence has suggested that the stochastic inversion of crosshole GPR data within a coupled geophysical-hydrological framework may allow for effective estimation of subsurface van-Genuchten-Mualem (VGM) parameters and their corresponding uncertainties. An important and still unresolved issue, however, is how to best integrate GPR data into a stochastic inversion in order to estimate the VGM parameters and their uncertainties, thus improving hydrological predictions. Recognizing the importance of this issue, the aim of the research presented in this thesis was to first introduce a fully Bayesian inversion called Markov-chain-Monte-carlo (MCMC) strategy to perform the stochastic inversion of steady-state GPR data to estimate the VGM parameters and their uncertainties. Within this study, the choice of the prior parameter probability distributions from which potential model configurations are drawn and tested against observed data was also investigated. Analysis of both synthetic and field data collected at the Eggborough (UK) site indicates that the geophysical data alone contain valuable information regarding the VGM parameters. However, significantly better results are obtained when these data are combined with a realistic, informative prior. A subsequent study explore in detail the dynamic infiltration case, specifically to what extent time-lapse ZOP GPR data, collected during a forced infiltration experiment at the Arrenaes field site (Denmark), can help to quantify VGM parameters and their uncertainties using the MCMC inversion strategy. The findings indicate that the stochastic inversion of time-lapse GPR data does indeed allow for a substantial refinement in the inferred posterior VGM parameter distributions. In turn, this significantly improves knowledge of the hydraulic properties, which are required to predict hydraulic behaviour. Finally, another aspect that needed to be addressed involved the comparison of time-lapse GPR data collected under different infiltration conditions (i.e., natural loading and forced infiltration conditions) to estimate the VGM parameters using the MCMC inversion strategy. The results show that for the synthetic example, considering data collected during a forced infiltration test helps to better refine soil hydraulic properties compared to data collected under natural infiltration conditions. When investigating data collected at the Arrenaes field site, further complications arised due to model error and showed the importance of also including a rigorous analysis of the propagation of model error with time and depth when considering time-lapse data. Although the efforts in this thesis were focused on GPR data, the corresponding findings are likely to have general applicability to other types of geophysical data and field environments. Moreover, the obtained results allow to have confidence for future developments in integration of geophysical data with stochastic inversions to improve the characterization of the unsaturated zone but also reveal important issues linked with stochastic inversions, namely model errors, that should definitely be addressed in future research.