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Event of the same type occurring several times for one individual (recurrent events) are present in various domains (industrial systems reliability, episodes of unemployment, political conflicts, chronic diseases episodes). Analysis of such kind of data should account for the whole recurrence process dynamics rather than only focusing on the number of observed events. Statistical models for recurrent events analysis are developed in the counting process probabilistic framework. One of the often-used models is the Andersen-Gill model, a generalization of the well-known Cox model for durations, which assumes that the baseline intensity of the recurrence process is time-dependent and is adjusted for covariates. For an individual i with covariates Xi, the intensity is as follows: $\lambda$_{ik}(t;$\theta$) = $\lambda$_0(t) exp (X_i $\beta$). The baseline intensity can be specified parametrically, in a form of Weibull: $\lambda$_0 (t) = $\gamma$_{1} $\gamma$_{2} t^{$\gamma$_2-1}, with $\gamma$1 scale parameter et $\gamma$2 shape parameter. However, the observed covariates are often insufficient to explain the observed heterogeneity in data. This is often the case of clinical trials data containing information on patients. In this article a mixture model for recurrent events analysis is proposed. This model allows to account for unobserved heterogeneity and to cluster individuals according to their recurrence process. The intensity of the process is parametrically specified within each class and depend on observed covariates. Thus, the intensity becomes specific to class k: $\lambda$_{ik} (t; $\theta$_k) = $\gamma$_{1k} $\gamma$_{2k} t^{$\gamma$_{2k}-1} exp (X_i $\beta$_k). The model parameters are estimated by the Maximum Likelihood method, using the EM algorithm. The BIC criterion is employed to choose the optimal number of classes. Model feasibility is verified by Monte Carlo simulations. An application to real data concerning hospital readmissions of elderly patients is proposed. The proposed model feasibility is empirically verified (the optimization algorithm converges, providing non-biased estimates). The real data application allows to identify two clinically relevant classes of patients.

Hephaestin (Hp) is a trans-membrane protein, which plays a critical role in intestinal iron absorption. Hp was originally identified as the gene responsible for the phenotype of sex-linked anaemia in theslamouse. The mutation in theslaprotein causes accumulation of dietary iron in duodenal cells, causing severe microcytic hypochromic anaemia. Although mucosal uptake of dietary iron is normal, export from the duodenum is inhibited. Hp is homologous to ceruloplasmin (Cp), a member of the family of multi copper ferroxidases (MCFs) and possesses ferroxidase activity that facilitates iron release from the duodenum and load onto the serum iron transport protein transferrin. In the present study, attempts were made to produce biologically active recombinant mouse hephaestin as a secretory form tagged with green fluorescent protein (GFP), Hpsec-GFP. Plasmid expressing Hpsec-GFP was constructed and transfected into COS and CHO cells. The GFP aided the monitoring expression in real time to select the best conditions to maximise expression and provided a tag for purifying and analysing Hpsec-GFP. The protein had detectable oxidase activity as shown by in-gel and solution-based assays. The methods described here can provide the basis for further work to probe the interaction of hephaestin with other proteins using complementary fluorescent tags on target proteins that would facilitate the fluorescence resonance energy transfer measurements, for example with transferrin or colocalisation studies, and help to discover more about hephaestin works at the molecular level.

ABSTRACTThis paper is about turn exchanges, the structure of speaking turns and the relationship of nonverbal behavior to both exchanges and turns. Its purpose is to present a conceptual framework for analyzing and interpreting turn exchange and speaking turns, and data are cited when possible. First discussed are specific forms of exchange such as “smooth” and “simultaneous.” The Praguean concept of functional differentiation is invoked to argue that forms of turn exchange have indexical value. The relationship of nonverbal behavior to turn exchange is then discussed. An analysis of videotaped, dyadic interactions between strangers, “getting acquainted” conversation, is reported in order to demonstrate that the nonoverlapping exchange has structurally, hence indexically. distinct forms. These forms, defined by both verbal and nonverbal elements, are ordered in a hierarchy of pragmatic markedness. It is concluded that differentiating pragmatic markedness in conversational patterns is a powerful device for determining indexical features of conversation and thus of relevance for a semiotic understanding of everyday speech.