Adeno-associated virus (AAV) vectors achieve prolonged transgene expression in mouse myocardium and arteries in vivo: a comparative study with adenovirus vectors.

Plasmid DNA and adenovirus vectors currently used in cardiovascular gene therapy trials are limited by low efficiency and short-lived transgene expression, respectively. Recombinant adeno-associated virus (AAV) has recently emerged as an attractive vector for cardiovascular gene therapy. In the present study, we have compared AAV and adenovirus vectors with respect to gene transfer efficiency and the duration of transgene expression in mouse hearts and arteries in vivo. AAV vectors (titer: 5 x 10(8) transducing units (TU)/ml) and adenovirus vectors (1.2 x 10(10) TU/ml) expressing a green fluorescent protein (EGFP) gene were injected either intramyocardially (n=32) or intrapericardially (n=3) in CD-1 mice. Hearts were harvested at varying time intervals (3 days to 1 year) after gene delivery. After intramyocardial injection of 5 microl virus stock solution, cardiomyocyte transduction rates with AAV vectors were 4-fold lower than with adenovirus vectors (1.5% (range: 0.5-2.6%) vs. 6.2% (range: 2.7-13.7%); P<0.05), but similar to titer-matched adenovirus vectors (0.7%; range: 0.2-1.2%). AAV-mediated EGFP expression lasted for at least 1 year. AAV vectors instilled into the pericardial space transduced epicardial myocytes. Arterial gene transfer was studied in mouse carotids (n=26). Both vectors selectively transduced endothelial cells after luminal instillation. Transduction rates with AAV vectors were 8-fold lower than with adenovirus vectors (2.0% (range: 0-3.2%) vs. 16.2% (range: 8.5-20.2%); P<0.05). Prolonged EGFP expression was observed after AAV but not adenovirus-mediated gene transfer. In conclusion, AAV vectors deliver and express genes for extended periods of time in the myocardium and arterial endothelium in vivo. AAV vectors may be useful for gene therapy approaches to chronic cardiovascular diseases.

Example-based support vector machine for drug concentration analysis

Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. In this paper, we focus on the prediction of drug concentrations using Support Vector Machines (S VM) and the analysis of the influence of each feature to the prediction results. Our study shows that SVM-based approaches achieve similar prediction results compared with pharmacokinetic model. The two proposed example-based SVM methods demonstrate that the individual features help to increase the accuracy in the predictions of drug concentration with a reduced library of training data.

Molecular basis of selective PPARgamma modulation for the treatment of Type 2 diabetes.

Peroxisome proliferator-activated receptors (PPARs) (alpha, beta/delta and gamma) are lipid sensors capable of adapting gene expression to integrate various lipid signals. As such, PPARs are also very important pharmaceutical targets, and specific synthetic ligands exist for the different isotypes and are either currently used or hold promises in the treatment of major metabolic disorders. In particular, compounds of the class of the thiazolinediones (TZDs) are PPARgamma agonists and potent insulin-sensitizers. The specific but still broad expression patterns of PPARgamma, as well as its implication in numerous pathways, constitutes also a disadvantage regarding drug administration, since this potentially increases the chance to generate side-effects through the activation of the receptor in tissues or cells not affected by the disease. Actually, numerous side effects associated with the administration of TZDs have been reported. Today, a new generation of PPARgamma modulators is being actively developed to activate the receptor more specifically, in a cell and time-dependent manner, in order to induce a specific subset of target genes only and modulate a restricted number of metabolic pathways. We will discuss here why and how the development of such selective PPARgamma modulators is possible, and summarize the results obtained with the published molecules.

Modulation of proteasomal activity required for the generation of a cytotoxic T lymphocyte-defined peptide derived from the tumor antigen MAGE-3.

We have analyzed the presentation of human histocompatability leukocyte antigen-A*0201-associated tumor peptide antigen MAGE-3271-279 by melanoma cells. We show that specific cytotoxic T lymphocyte (CTL)-recognizing cells transfected with a minigene encoding the preprocessed fragment MAGE-3271-279 failed to recognize cells expressing the full length MAGE-3 protein. Digestion of synthetic peptides extended at the NH2 or COOH terminus of MAGE-3271-279 with purified human proteasome revealed that the generation of the COOH terminus of the antigenic peptide was impaired. Surprisingly, addition of lactacystin to purified proteasome, though partially inhibitory, resulted in the generation of the antigenic peptide. Furthermore, treatment of melanoma cells expressing the MAGE-3 protein with lactacystin resulted in efficient lysis by MAGE-3271-279-specific CTL. We therefore postulate that the generation of antigenic peptides by the proteasome in cells can be modulated by the selective inhibition of certain of its enzymaticactivities.

Wave-vector dependence of spin and density multipole excitations in quantum dots

We have employed time-dependent local-spin density-functional theory to analyze the multipole spin and charge density excitations in GaAs-AlxGa1-xAs quantum dots. The on-plane transferred momentum degree of freedom has been taken into account, and the wave-vector dependence of the excitations is discussed. In agreement with previous experiments, we have found that the energies of these modes do not depend on the transferred wave vector, although their intensities do. Comparison with a recent resonant Raman scattering experiment [C. Schüller et al., Phys. Rev. Lett. 80, 2673 (1998)] is made. This allows us to identify the angular momentum of several of the observed modes as well as to reproduce their energies

Gauge transformations in the Lagrangian and Hamilton formalisms of generally covariant theories

We study spacetime diffeomorphisms in the Hamiltonian and Lagrangian formalisms of generally covariant systems. We show that the gauge group for such a system is characterized by having generators which are projectable under the Legendre map. The gauge group is found to be much larger than the original group of spacetime diffeomorphisms, since its generators must depend on the lapse function and shift vector of the spacetime metric in a given coordinate patch. Our results are generalizations of earlier results by Salisbury and Sundermeyer. They arise in a natural way from using the requirement of equivalence between Lagrangian and Hamiltonian formulations of the system, and they are new in that the symmetries are realized on the full set of phase space variables. The generators are displayed explicitly and are applied to the relativistic string and to general relativity.

Variational analysis of the Gross-Neveu model in an S^1 space

The Gross-Neveu model in an S^1 space is analyzed by means of a variational technique: the Gaussian effective potential. By making the proper connection with previous exact results at finite temperature, we show that this technique is able to describe the phase transition occurring in this model. We also make some remarks about the appropriate treatment of Grassmann variables in variational approaches.