The Effects of Andrographolide on the Enhancement of Chondrogenesis and Osteogenesis in Human Suprapatellar Fat Pad Derived Mesenchymal Stem Cells

Andrographolide is a labdane diterpenoid herb, which is isolated from the leaves of Andrographis paniculata, and widely used for its potential medical properties. However, there are no reports on the effects of andrographolide on the human suprapatellar fat pad of osteoarthritis patients. In the present study, our goal was to evaluate the innovative effects of andrographolide on viability and Tri-lineage differentiation of human mesenchymal stem cells from suprapatellar fat pad tissues. The results revealed that andrographolide had no cytotoxic effects when the concentration was less than 12.5 µM. Interestingly, andrographolide had significantly enhanced, dose dependent, osteogenesis and chondrogenesis as evidenced by a significantly intensified stain for Alizarin Red S, Toluidine Blue and Alcian Blue. Moreover, andrographolide can upregulate the expression of genes related to osteogenic and chondrogenic differentiation, including Runx2, OPN, Sox9, and Aggrecan in mesenchymal stem cells from human suprapatellar fat pad tissues. In contrast, andrographolide suppressed adipogenic differentiation as evidenced by significantly diminished Oil Red O staining and expression levels for adipogenic-specific genes for PPAR-γ2 and LPL. These findings confirm that andrographolide can specifically enhance osteogenesis and chondrogenesis of mesenchymal stem cells from human suprapatellar fat pad tissues. It has potential as a therapeutic agent derived from natural sources for regenerative medicine.     

Efficient MCMC estimation of some elliptical copula regression models through scale mixtures of normals

This paper proposes an efficient estimation method for some elliptical copula regression models by expressing both copula density and marginal density functions as scale mixtures of normals (SMN). Implementing these models using the SMN is novel and allows efficient estimation via Bayesian methods. An innovative algorithm for the case of complex semicontinuous margins is also presented. We utilize the facts that copulas are invariant to the location and scale of the margins; all elliptical distributions have the same correlation structure; and some densities can be represented by the SMN. Two simulation studies, one on continuous margins and the other on semicontinuous margins, highlight the favorable performance of the proposed methods. Two empirical studies, one on the US excess returns and one on the Thai wage earnings, further illustrate the applicability of the proposals.     

Analyzing return asymmetry and quantiles through stochastic volatility models using asymmetric Laplace error via uniform scale mixtures

This paper proposes a new approach to analyze stock return asymmetry and quantiles. We also present a new scale mixture of uniform (SMU) representation for the asymmetric Laplace distribution (ALD). The use of the SMU for a probability distribution is a data augmentation technique that simplifies the Gibbs sampler of the Bayesian Markov chain Monte Carlo algorithms. We consider a stochastic volatility (SV) model with an ALD error distribution. With the SMU representation, the full conditional distribution for some parameters is shown to have closed form. It is also known that the ALD can be used to obtain the coefficients of quantile regression models. This paper also considers a quantile SV model by fixing the skew parameter of the ALD at specific quantile level. Simulation study shows that the proposed methodology works well in both SV and quantile SV models using Bayesian approach. In the empirical study, we analyze index returns of the stock markets in Australia, Japan, Hong Kong, Thailand, and the UK and study the effect of S&P 500 on these returns. The results show the significant return asymmetry in some markets and the influence by S&P 500 in all markets at all quantile levels. Copyright © 2014 John Wiley & Sons, Ltd.