Performance of AAV8 vectors expressing human factor IX from a hepatic-selective promoter following intravenous injection into rats

Background: Vectors based on adeno-associated virus-8 (AAV8) have shown efficiency and efficacy for liver-directed gene therapy protocols following intravascular injection, particularly in relation to haemophilia gene therapy. AAV8 has also been proposed for gene therapy targeted at skeletal and cardiac muscle, again via intravascular injection. It is important to assess vector targeting at the level of virion accumulation and transgene expression in multiple species to ascertain potential issues relating to species variation in infectivity profiles. Methods: We used AAV8 vectors expressing human factor IX (FIX) from the liver-specific LP-1 promoter and administered this virus via the intravascular route of injection into 12 week old Wistar Kyoto rats. We assessed FIX levels in serum by ELISA and transgene expression at sacrifice by immunohistochemistry using anti-FIX antibodies. Vector DNA levels in organs we determined by real time PCR. Results: Administration of 1 × 1011 or 5 × 1011 scAAV8-LP1-hFIX vector particles/rat resulted in efficient production of physiological hFIX levels, respectively in blood assessed 4 weeks post-injection. This was maintained for the 4 month duration of the study. At 4 months we observed liver persistence of vector with minimal non-hepatic distribution. Conclusion: Our results demonstrate that AAV8 is a robust vector for delivering therapeutic genes into rat liver following intravascular injection

Nuclear Structure Calculations with Low-Momentum Potentials in a Model Space Truncation Approach

We have calculated the ground-state energy of the doubly magic nuclei 4He, 16O and 40Ca within the framework of the Goldstone expansion starting from various modern nucleon-nucleon potentials. The short-range repulsion of these potentials has been renormalized by constructing a low-momentum potential V-low-k. We have studied the connection between the cutoff momemtum Lambda and the size of the harmonic oscillator space employed in the calculations. We have found a fast convergence of the results with a limited number of oscillator quanta.Comment: 6 pages, 8 figures, to be published on Physical Review

Shell-model study of the N=82 isotonic chain with a realistic effective hamiltonian

We have performed shell-model calculations for the even- and odd-mass N=82 isotones, focusing attention on low-energy states. The single-particle energies and effective two-body interaction have been both determined within the framework of the time-dependent degenerate linked-diagram perturbation theory, starting from a low-momentum interaction derived from the CD-Bonn nucleon-nucleon potential. In this way, no phenomenological input enters our effective Hamiltonian, whose reliability is evidenced by the good agreement between theory and experiment.Comment: 7 pages, 11 figures, 3 tables, to be published in Physical Review

On the relation between low-energy constants and resonance saturation

Although there are phenomenological indications that the low-energy constants in the chiral lagrangian may be understood in terms of a finite number of hadronic resonances, it remains unclear how this follows from QCD. One of the arguments usually given is that low-energy constants are associated with chiral symmetry breaking, while QCD perturbation theory suggests that at high energy chiral symmetry is unbroken, so that only low-lying resonances contribute to the low-energy constants. We revisit this argument in the limit of large Nc, discussing its validity in particular for the low-energy constant L8, and conclude that QCD may be more subtle that what this argument suggests. We illustrate our considerations in a simple Regge-like model which also applies at finite Nc.Comment: 15 pages, one figur

MULTIPAC, a multiple pool processor and computer for a spacecraft central data system, phase 2 Final report

MULTIPAC, multiple pool processor and computer for deep space probe central data syste

Power spectra methods for a stochastic description of diffusion on deterministically growing domains

A central challenge in developmental biology is understanding the creation of robust spatiotemporal heterogeneity. Generally, the mathematical treatments of biological systems have used continuum, mean-field hypotheses for their constituent parts, which ignores any sources of intrinsic stochastic effects. In this paper we consider a stochastic space-jump process as a description of diffusion, i.e., particles are able to undergo a random walk on a discretized domain. By developing analytical Fourier methods we are able to probe this probabilistic framework, which gives us insight into the patterning potential of diffusive systems. Further, an alternative description of domain growth is introduced, with which we are able to rigorously link the mean-field and stochastic descriptions. Finally, through combining these ideas, it is shown that such stochastic descriptions of diffusion on a deterministically growing domain are able to support the nucleation of states that are far removed from the deterministic mean-field steady state

Stochastic reaction & diffusion on growing domains: understanding the breakdown of robust pattern formation

Many biological patterns, from population densities to animal coat markings, can be thought of as heterogeneous spatiotemporal distributions of mobile agents. Many mathematical models have been proposed to account for the emergence of this complexity, but, in general, they have consisted of deterministic systems of differential equations, which do not take into account the stochastic nature of population interactions. One particular, pertinent criticism of these deterministic systems is that the exhibited patterns can often be highly sensitive to changes in initial conditions, domain geometry, parameter values, etc. Due to this sensitivity, we seek to understand the effects of stochasticity and growth on paradigm biological patterning models. In this paper, we extend spatial Fourier analysis and growing domain mapping techniques to encompass stochastic Turing systems. Through this we find that the stochastic systems are able to realize much richer dynamics than their deterministic counterparts, in that patterns are able to exist outside the standard Turing parameter range. Further, it is seen that the inherent stochasticity in the reactions appears to be more important than the noise generated by growth, when considering which wave modes are excited. Finally, although growth is able to generate robust pattern sequences in the deterministic case, we see that stochastic effects destroy this mechanism for conferring robustness. However, through Fourier analysis we are able to suggest a reason behind this lack of robustness and identify possible mechanisms by which to reclaim it

Influence of stochastic domain growth on pattern nucleation for diffusive systems with internal noise

Numerous mathematical models exploring the emergence of complexity within developmental biology incorporate diffusion as the dominant mechanism of transport. However, self-organizing paradigms can exhibit the biologically undesirable property of extensive sensitivity, as illustrated by the behavior of the French-flag model in response to intrinsic noise and Turing’s model when subjected to fluctuations in initial conditions. Domain growth is known to be a stabilizing factor for the latter, though the interaction of intrinsic noise and domain growth is underexplored, even in the simplest of biophysical settings. Previously, we developed analytical Fourier methods and a description of domain growth that allowed us to characterize the effects of deterministic domain growth on stochastically diffusing systems. In this paper we extend our analysis to encompass stochastically growing domains. This form of growth can be used only to link the meso- and macroscopic domains as the “box-splitting” form of growth on the microscopic scale has an ill-defined thermodynamic limit. The extension is achieved by allowing the simulated particles to undergo random walks on a discretized domain, while stochastically controlling the length of each discretized compartment. Due to the dependence of diffusion on the domain discretization, we find that the description of diffusion cannot be uniquely derived. We apply these analytical methods to two justified descriptions, where it is shown that, under certain conditions, diffusion is able to support a consistent inhomogeneous state that is far removed from the deterministic equilibrium, without additional kinetics. Finally, a logistically growing domain is considered. Not only does this show that we can deal with nonmonotonic descriptions of stochastic growth, but it is also seen that diffusion on a stationary domain produces different effects to diffusion on a domain that is stationary “on average.