Mesenchymal stem cells and cell-free preparations for treating atopic dermatitis

Atopic dermatitis (AD) is a chronic cutaneous inflammatory disease caused by an interaction between genetic, immune and epidermal barrier factors. Several treatments can be used to treat this disease but there are patients that do not respond to actual drugs. So, there is a need to develop effective therapies for AD. Mesenchymal stem cells (MSCs) are non-hematopoietic multipotent adult progenitor cells with immunomodulatory power and self-regenerating capacity to repair tissue damage, so they could be a potential effective treatment for AD. MSCs-Conditioned Medium (CM) and MSCs-exosomes are cell-free preparation with molecules secreted by stem cells that could be also beneficial for AD. This viewpoint reviews the actual development of MSCs, MSCs-CM and MSCs-exosomes for treating patients with AD.     

Diagnostic Checking in a Flexible Nonlinear Time Series Model

This paper considers a sequence of misspecification tests for a flexible nonlinear time series model. The model is a generalization of both the smooth transition autoregressive (STAR) and the autoregressive artificial neural network (AR-ANN) models. The tests are Lagrange multiplier (LM) type tests of parameter constancy against the alternative of smoothly changing ones, of serial independence, and of constant variance of the error term against the hypothesis that the variance changes smoothly between regimes. The small sample behaviour of the proposed tests is evaluated by a Monte-Carlo study and the results show that the tests have size close to the nominal one and a good power.     

Nonlinear error correction models

The relationship between cointegration and error correction (EC) models is well characterized in a linear context, but the extension to the nonlinear context is still a challenge. Few extensions of the linear framework have been done in the context of nonlinear error correction (NEC) or asymmetric and time varying error correction models. In this paper, we propose a theoretical framework based on the concept of near epoch dependence (NED) that allows us to formally address these issues. In particular, we partially extend the Granger Representation Theorem to the nonlinear case.     

COMBINED QUALITATIVE/QUANTITATIVE SIMULATION MODELS OF CONTINUOUS-TIME PROCESSES USING FUZZY INDUCTIVE REASONING TECHNIQUES

Abstract

A new mixed quantitative and qualitative simulation methodology based on fuzzy inductive reasoning is presented. The feasibility of this methodology is demonstrated by means of a simple hydraulic control system. The mechanical and electrical parts of the control system are modeled using differential equations, whereas the hydraulic part is modeled using fuzzy inductive reasoning. The technique is described in detail in the first part of this paper. The example is shown in the second part of the paper. The mixed quantitative and qualitative model is simulated in ACSL, and the simulation results are compared with those obtained from a fully quantitative model. The example was chosen as a simple to describe, yet numerically demanding process whose sole purpose is to prove the concept. Several practical applications of this mixed modeling technique are mentioned in the paper. but their realization has not yet been completed