Specification and testing of multiplicative time-varying GARCH models with applications

In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smoothly over time. This nonstationary component is defined as a linear combination of logistic transition functions with time as the transition variable. The appropriate number of transition functions is determined by a sequence of specification tests. For that purpose, a coherent modelling strategy based on statistical inference is presented. It is heavily dependent on Lagrange multiplier type misspecification tests. The tests are easily implemented as they are entirely based on auxiliary regressions. Finite-sample properties of the strategy and tests are examined by simulation. The modelling strategy is illustrated in practice with two real examples: an empirical application to daily exchange rate returns and another one to daily coffee futures returns.

Xenogeneic M2-polarization of Macrophages by undifferentiated and differentiated adipose tissue-derived stem cells

Mesenchymal stem cells (MSCs) are considered to be â â immunologically privileged.â â In a previous work when human adipose tissue-derived stem cells (hASCs) subcutaneously implanted in mice we did not identify an adverse host response1. Recently, it was shown that tissue regeneration could benefit from the polarization of M2 macrophages subpopulations 2. In this study we hypothesised that undifferentiated hASCs and derived osteoblasts and chondrocytes are able to switch murine bone marrow-derived macrophages (mBMMÃ s) into M2 phenotype, aiding tissue regeneration. Murine BMMÃ s were plated in direct contact with undifferentiated and osteo or chondro-differentiated hASCs for 4 h, 10 h, 24 h and 72 h. The cytokine profile was analysed by qRT-PCR and the surface markers were detected by flow cytometry. The direct interaction of both cell types was observed by time lapse microscopy. The results showed that mBMMÃ s polarized after contacting tissue culture polystyrene. This M2 phenotype was maintained along the experiment in direct contact with both undifferentiated and osteo or chondro-differentiated hASCs. This was confirmed by the expression of IL-1, IL-10, IL-4, TNF-a and IFN-g (genetic profile) and surface markers (CD206 + + , CD336 + + , MHC II + and CD86 + + ) detection. These data suggest the potential of hASCs in contemporary xenogenic tissue engineering and regenerative medicine strategies, as well as host immune system modulation in autoimmune diseases. 

Microstructure and mechanical properties of carbon nanotube reinforced cementitious composites developed using a novel dispersion technique

The authors also acknowledge Centre for Textile Science and Technology (University of Minho) and FIBRENAMICS PLATFORMfor providing required conditions for this research. Sincere thanks are also due to Mr. Pedro Samuel Leite and Mr. Carlos Jesus for their kind help in sample preparation and testing.

Nanotechnological approaches using curcumin and Withania somnifera: neuroprotection and antimicrobial activities

Tese de Doutoramento em Biologia de Plantas

New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemaking

During must fermentation by Saccharomyces cerevisiae strains thousands of volatile aroma compounds are formed. The objective of the present work was to adapt computational approaches to analyze pheno-metabolomic diversity of a S. cerevisiae strain collection with different origins. Phenotypic and genetic characterization together with individual must fermentations were performed, and metabolites relevant to aromatic profiles were determined. Experimental results were projected onto a common coordinates system, revealing 17 statistical-relevant multi-dimensional modules, combining sets of most-correlated features of noteworthy biological importance. The present method allowed, as a breakthrough, to combine genetic, phenotypic and metabolomic data, which has not been possible so far due to difficulties in comparing different types of data. Therefore, the proposed computational approach revealed as successful to shed light into the holistic characterization of S. cerevisiae pheno-metabolome in must fermentative conditions. This will allow the identification of combined relevant features with application in selection of good winemaking strains.