The traditional way of studying temporal networks is to aggregate the dynamics of the edges to create a static weighted network. This implicitly assumes that the edges are governed by Poisson processes, which is not typically the case in empirical temporal networks. Accordingly, we examine the effects of non-Poisson inter-event statistics on the dynamics of edges, and we apply the concept of a generalized master equation to the study of continuous-time random walks on networks. We show that this equation reduces to the standard rate equations when the underlying process is Poissonian and that its stationary solution is determined by an effective transition matrix whose leading eigenvector is easy to calculate. We conduct numerical simulations and also derive analytical results for the stationary solution under the assumption that all edges have the same waiting-time distribution. We discuss the implications of our work for dynamical processes on temporal networks and for the construction of network diagnostics that take into account their nontrivial stochastic nature.
Summary.In a single-centre study the feasibility and efficacy of repeated antilymphocyte globulin (ALG) for patients with severe aplastic anaemia (SAA) not responding to an initial ALG treatment or relapsing after initial response to ALG was evaluated. 139 consecutive patients with newly diagnosed SAA were treated with ALG between 1976 and 1995. 89 patients responded to a first course; 50 patients did not become transfusion independent. Of the 89 responders, 66 remained in remission, 23 relapsed. 43 patients received a second or subsequent course of ALG for failure to respond (n ¼ 25) or relapse (n ¼ 18) and were given a total of 53 courses. Acute reactions in the multiply exposed patients occurred during the first ALG treatment in 11 (26%) and during subsequent exposures in 16/53 courses (30%; P > 0·2). Incidence of serum sickness was 63% (27/43) after the initial course compared to 57% (30/53) after subsequent courses (P > 0·2), but clinical signs of serum sickness occurred earlier after repeated (median 6 d) as compared to initial exposure (13 d; P ¼ 0·008). Transfusion-independent haemopoiesis was achieved in 27/43 (63%) and survival probabilities for the 43 patients receiving multiple courses of ALG was 52 Ϯ 8% at 10 years. The probability of developing a late clonal disorder was 53 Ϯ 10% after multiple, as compared to 34 Ϯ 7% after single exposure (P ¼ 0·15). No difference in results was observed between patients retreated for failure to first ALG or for relapse. ALG of the same species can be repeated without increased risks of side-effects in patients with SAA. A second or subsequent course of ALG from the same source can be effective when the first course has failed.
We develop a Bayesian hierarchical modelling approach for cosmic shear power spectrum inference, jointly sampling from the posterior distribution of the cosmic shear field and its (tomographic) power spectra. Inference of the shear power spectrum is a powerful intermediate product for a cosmic shear analysis, since it requires very few model assumptions and can be used to perform inference on a wide range of cosmological models a posteriori without loss of information. We show that joint posterior for the shear map and power spectrum can be sampled effectively by Gibbs sampling, iteratively drawing samples from the map and power spectrum, each conditional on the other. This approach neatly circumvents difficulties associated with complicated survey geometry and masks that plague frequentist power spectrum estimators, since the power spectrum inference provides prior information about the field in masked regions at every sampling step. We demonstrate this approach for inference of tomographic shear E-mode, B-mode and EB-cross power spectra from a simulated galaxy shear catalogue with a number of important features; galaxies distributed on the sky and in redshift with photometric redshift uncertainties, realistic random ellipticity noise for every galaxy and a complicated survey mask. The obtained posterior distributions for the tomographic power spectrum coefficients recover the underlying simulated power spectra for both E-and B-modes.
Rationale: A reduced rate of myocardial infarction has been reported in patients with atrial fibrillation treated with FXa (factor Xa) inhibitors including rivaroxaban compared with vitamin K antagonists. At the same time, low-dose rivaroxaban has been shown to reduce mortality and atherothrombotic events in patients with coronary artery disease. Yet, the mechanisms underlying this reduction remain unknown. Objective: In this study, we hypothesized that rivaroxaban’s antithrombotic potential is linked to a hitherto unknown rivaroxaban effect that impacts on platelet reactivity and arterial thrombosis. Methods and Results: In this study, we identified FXa as potent, direct agonist of the PAR-1 (protease-activated receptor 1), leading to platelet activation and thrombus formation, which can be inhibited by rivaroxaban. We found that rivaroxaban reduced arterial thrombus stability in a mouse model of arterial thrombosis using intravital microscopy. For in vitro studies, atrial fibrillation patients on permanent rivaroxaban treatment for stroke prevention, respective controls, and patients with new-onset atrial fibrillation before and after first intake of rivaroxaban (time series analysis) were recruited. Platelet aggregation responses, as well as thrombus formation under arterial flow conditions on collagen and atherosclerotic plaque material, were attenuated by rivaroxaban. We show that rivaroxaban’s antiplatelet effect is plasma dependent but independent of thrombin and rivaroxaban’s anticoagulatory capacity. Conclusions: Here, we identified FXa as potent platelet agonist that acts through PAR-1. Therefore, rivaroxaban exerts an antiplatelet effect that together with its well-known potent anticoagulatory capacity might lead to reduced frequency of atherothrombotic events and improved outcome in patients.
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