Pulmonary artery denervation using catheter based ultrasonic energy

AIMS: Pulmonary arterial hypertension is a devastating disease characterized by pulmonary vascular remodelling and right heart failure. Radio-frequency pulmonary artery denervation (PDN) improves pulmonary hemodynamics in pre-clinical and early clinical studies, however denervation depth is limited. High-frequency non-focused ultrasound can deliver energy to the vessel adventitia, sparing the intima and media. We therefore investigated the feasibility, safety and efficacy of ultrasound PDN. METHODS AND RESULTS: Histological examination demonstrated that innervation of human pulmonary arteries are predominantly sympathetic (71%), with >40% of nerves at a depth of >4mm. Finite element analysis of ultrasound energy distribution and ex-vivo studies demonstrated generation of temperatures >47ºC to a depth of 10mm. In domestic swine PDN reduced mean pulmonary artery pressure induced by thromboxane A2 in comparison to sham. No adverse events were observed to 95-days. Histological examination identified structural and immunohistological alterations of nerves in PDN treated animals, with sparing of the intima and media and reduced tyrosine hydroxylase staining 95-days post-procedure indicating persistent alteration of the structure of sympathetic nerves. CONCLUSIONS: Ultrasound PDN is safe and effective in the pre-clinical setting, with energy delivery to a depth that will permit targeting sympathetic nerves in humans

The total quasi-steady-state approximation for fully competitive enzyme reactions

none3The validity of the Michaelis-Menten-Briggs-Haldane approximation for single enzyme reactions has recently been improved by the formalism of the total quasi-steady-state approximation. This approach is here extended to fully competitive systems, and a criterion for its validity is provided. We show that it extends the Michaelis-Menten-Briggs-Haldane approximation for such systems for a wide range of parameters very convincingly, and investigate special cases. It is demonstrated that our method is at least roughly valid in the case of identical affinities. The results presented should be useful for numerical simulations of many in vivo reactions.noneM. PEDERSEN; BERSANI AM; BERSANI EPedersen, MORTEN GRAM; Bersani, Am; Bersani, E

Ribozymes: Analytical Solution of the One-substrate, Two-intermediate Reversible Scheme for Enzyme Reactions

The paper presents a kinetic analysis of a reversible enzymatic reaction S⇄P involving two intermediate compounds under the condition [E]0 ≫ [S]0 + [P]0. For the case of mono-exponential behavior, we derive an equation for kobs as a function of [E]0, which emphasizes the pitfalls of oversimplifying kinetic schemes (such as the Michaelis-Menten model) for ribozyme studies. This novel apparent rate constant, which has been arrived at through mechanistic considerations, is analyzed, and the characteristic parameters obtained. The equation, which seems to fit experimental data better than conventional approximations, is used to analyze a single turnover study on an ADC1 ribozyme drawn from hepatitis delta virus RNA. The microscopic kinetic constants for such enzyme are evaluated and its mono-exponential behavior verified

Modelling the Human Immune System by Combining Bioinformatics and Systems Biology Approaches

Over the past decade a number of bioinformatics tools have been developed that use genomic sequences as input to predict to which parts of a microbe the immune system will react, the so-called epitopes. Many predicted epitopes have later been verified experimentally, demonstrating the usefulness of such predictions. At the same time, simulation models have been developed that describe the dynamics of different immune cell populations and their interactions with microbes. These models have been used to explain experimental findings where timing is of importance, such as the time between administration of a vaccine and infection with the microbe that the vaccine is intended to protect against. In this paper, we outline a framework for integration of these two approaches. As an example, we develop a model in which HIV dynamics are correlated with genomics data. For the first time, the fitness of wild type and mutated virus are assessed by means of a sequence-dependent scoring matrix, derived from a BLOSUM matrix, that links protein sequences to growth rates of the virus in the mathematical model. A combined bioinformatics and systems biology approach can lead to a better understanding of immune system-related diseases where both timing and genomic information are of importance

Quasi steady-state approximations in complex intracellular signal transduction networks - a word of caution

Enzyme reactions play a pivotal role in intracellular signal transduction. Many enzymes are known to possess Michaelis\u2013Menten (MM) kinetics and the MM approximation is often used when modeling enzyme reactions. However, it is known that the MM approximation is only valid at low enzyme concentrations, a condition not fulfilled in many in vivo situations. Recently the total quasi steady-state approximation (tQSSA) has been developed for enzymes with MM kinetics. This new approximation is valid not only whenever the MM approximation is, but moreover in a greatly extended parameter range. Starting from a single reaction and arriving at the mitogen activated protein kinase (MAPK) cascade, we give several examples of biologically realistic scenarios where the MM approximation leads to quantitatively as well as qualitatively wrong conclusions, and show that the tQSSA improves the accuracy of the simulations greatly