Hydrodynamic evaluation of kangaroo aortic valve matrices for tissue valve engineering

We evaluated the hydrodynamic performance of kangaroo aortic valve matrices (KMs) (19, 21, and 23 mm), as potential scaffolds in tissue valve engineering using a pulsatile left heart model at low and high cardiac outputs (COs) and heart rates (HRs) of 60 and 90 beats/min. Data were measured in two samples of each type, pooled in two CO levels (2.1 +/- 0.7 and 4.2 +/- 0.6 L/min; mean +/- standard errors on the mean), and analyzed using analysis of variance with CO level, HR, and valve type as fixed factors and compared to similar porcine matrices (PMs). Transvalvular pressure gradient (Delta P) was a function of HR (P < 0.001) and CO (P < 0.001) but not of valve type (P = 0.39). Delta P was consistently lower in KMs but not significantly different from PMs. The effective orifice area and performance index of kangaroo matrices was statistically larger for all sizes at both COs and HRs.

A scalarization technique for computing the power and exponential moments of gaussian random matrices

We consider the problems of computing the power and exponential moments EXs and EetX of square Gaussian random matrices X=A+BWC for positive integer s and real t, where W is a standard normal random vector and A, B, C are appropriately dimensioned constant matrices. We solve the problems by a matrix product scalarization technique and interpret the solutions in system-theoretic terms. The results of the paper are applicable to Bayesian prediction in multivariate autoregressive time series and mean-reverting diffusion processes.

Inorganic nanoparticles as carriers for efficient cellular delivery

Cellular delivery involving the transfer of various drugs and bio-active molecules (peptides, proteins and DNAs, etc.) through the cell membrane into cells has attracted increasing attention because of its importance in medicine and drug delivery. This topic has been extensively reviewed. The direct delivery of drugs and biomolecules, however, is generally inefficient and suffering from problems such as enzymic degradation of DNAs. Therefore, searching for efficient and safe transport vehicles (carriers) to delivery genes or drugs into cells has been challenging yet exciting area of research. In past decades, many carriers have been developed and investigated extensively which can be generally classified into four major groups: viral carriers, organic cationic compounds, recombinant protiens and inorganic nanoparticles. Many inorganic materials, such as calcium phosphate, gold, carbon materials, silicon oxide, iron oxide and layered double hydroxide (LDH), have been studied. Inorganic nanoparticles show low toxicity and promise for controlled delivery properties, thus presenting a new alternative to viral carriers and cationic carriers. Inorganic nanoparticles generally possess versatile properties suitable for cellular delivery, including wide availability, rich functionality, good biocompatibility, potential capability of targeted delivery (e.g. selectively destroying cancer cells but sparing normal tissues) and controlled release of carried drugs. This paper reviews the latest advances in inorganic nanoparticle applications as cellular delivery carriers and highlights some key issues in efficient cellular delivery using inorganic nanoparticles. Critical proper-ties of inorganic nanoparticles, surface functionalisation (modification), uptake of biomolecules, the driving forces for delivery, and release of biomolecules will be reviewed systematically. Selected examples of promising inorganic nanoparticle delivery systems, including gold, fullerences and carbon nanotubes, LDH and various oxide nanoparticles in particular their applications for gene delivery will be discussed. The fundamental understanding of properties of inorganic nanoparticles in relation to cellular delivery efficiency as the most paramount issue will be highlighted. (c) 2005 Elsevier Ltd. All rights reserved.

Mutation analysis to verify feature matrices for isolating errors in simulation models

Software simulation models are computer programs that need to be verified and debugged like any other software. In previous work, a method for error isolation in simulation models has been proposed. The method relies on a set of feature matrices that can be used to determine which part of the model implementation is responsible for deviations in the output of the model. Currrently these feature matrices have to be generated by hand from the model implementation, which is a tedious and error-prone task. In this paper, a method based on mutation analysis, as well as prototype tool support for the verification of the manually generated feature matrices is presented. The application of the method and tool to a model for wastewater treatment shows that the feature matrices can be verified effectively using a minimal number of mutants.