Atopic Dermatitis Host and Environment Model: Revisiting Therapeutic Options

Atopic Dermatitis affects both children and adults and is a serious health concern in many countries. AD is a complex disease with host and environmental factors underlying its pathology. Its treatment is multidimensional reflecting the diverse nature of its triggers and includes emollients, topical steroids and calcineurin inhibitors among others. Immunological dysfunction can be addressed broadly with systemic immunosupressors and specifically with monoclonal antibodies. Dupilumab, which targets IL-4 and IL-13 was granted approval for treatment of moderate-to-severe AD. Biologics targeting IgE/Th2 pathways may have its role in patients with overlapping AD and asthma. Psychological distress can exacerbate symptoms and is associated with increased severity of AD. Environmental triggers, such as, allergens can be addressed in selected cases with allergic immunotherapy. In this paper, we discuss AD treatment and propose a new step-by-step approach aiming at maintaining disease control and improving quality of life.info:eu-repo/semantics/publishedVersio

A dynamical point of view of Quantum Information: entropy and pressure

Quantum Information is a new area of research which has been growing rapidly since last decade. This topic is very close to potential applications to the so called Quantum Computer. In our point of view it makes sense to develop a more "dynamical point of view" of this theory. We want to consider the concepts of entropy and pressure for "stationary systems" acting on density matrices which generalize the usual ones in Ergodic Theory (in the sense of the Thermodynamic Formalism of R. Bowen, Y. Sinai and D. Ruelle). We consider the operator $\mathcal{L}$ acting on density matrices $\rho\in \mathcal{M}_N$ over a finite $N$-dimensional complex Hilbert space $\mathcal{L}(\rho):=\sum_{i=1}^k tr(W_i\rho W_i^*)V_i\rho V_i^*,$ where $W_i$ and $V_i$, $i=1,2,...k$ are operators in this Hilbert space. $\mathcal{L}$ is not a linear operator. In some sense this operator is a version of an Iterated Function System (IFS). Namely, the $V_i\,(.)\,V_i^*=:F_i(.)$, $i=1,2,...,k$, play the role of the inverse branches (acting on the configuration space of density matrices $\rho$) and the $W_i$ play the role of the weights one can consider on the IFS. We suppose that for all $\rho$ we have that $\sum_{i=1}^k tr(W_i\rho W_i^*)=1$. A family $W:=\{W_i\}_{i=1,..., k}$ determines a Quantum Iterated Function System (QIFS) $\mathcal{F}_{W}$, $\mathcal{F}_W=\{\mathcal{M}_N,F_i,W_i\}_{i=1,..., k}.

Is there a propeller neutron star in γ\gamma Cas?

$\gamma$ Cas is the prototype of a small population of B0-B1.5 III-V classical Be (cBe) stars that emit anomalous and hard X-rays with a unique array of properties. $\gamma$ Cas is known to host, like other cBe stars, a decretion disk and also a low mass companion. Recently Postnov et al. have posited that this companion is a magnetized rapidly spinning neutron star that deflects direct gravitational accretion from a stellar/disk wind via the "propeller mechanism." These authors state that the key X-ray observations are "remarkably well produced" in this scenario. We reexamine this mechanism in detail and conclude that there are a number of fatal objections in its application to the $\gamma$ Cas case. Among other considerations these issues include the prediction under the propeller scenario of a much smaller population of $\gamma$ Cas stars than is observed and the lack of allowance for observed correlations of X-ray and UV and/or optical properties over a variety of timescales.Comment: 9 page

A dynamical point of view of Quantum Information: Wigner measures

We analyze a known version of the discrete Wigner function and some connections with Quantum Iterated Funcion Systems. This paper is a follow up of "A dynamical point of view of Quantum Information: entropy and pressure" by the same authors

MCMC Bayesian Estimation in FIEGARCH Models

Bayesian inference for fractionally integrated exponential generalized autoregressive conditional heteroskedastic (FIEGARCH) models using Markov Chain Monte Carlo (MCMC) methods is described. A simulation study is presented to access the performance of the procedure, under the presence of long-memory in the volatility. Samples from FIEGARCH processes are obtained upon considering the generalized error distribution (GED) for the innovation process. Different values for the tail-thickness parameter \nu are considered covering both scenarios, innovation processes with lighter (\nu2) tails than the Gaussian distribution (\nu=2). A sensitivity analysis is performed by considering different prior density functions and by integrating (or not) the knowledge on the true parameter values to select the hyperparameter values