Supremacía del derecho federal sobre el Common Law en materia de requisitos de seguridad y eficacia terapéutica de productos sanitarios. Comentario a Riegel v. Medtronic, Inc. [552 U.S.__ (2008); February 20, 2008]

En Riegel v. Medtronic Inc. (552 U.S.__2008; February 20, 2008), el Sr. Riegel tuvo que ser sometido a un by-pass como consecuencia de la rotura del catéter, fabricado por Medtronic, con el que su médico le practicaba una angioplastia. A pesar de que el catéter había obtenido la autorización de comercialización de la FDA y cumplía los requisitos de seguridad previstos por el sistema regulatorio federal, el Sr. Riegel y su mujer interpusieron una acción de daños contra Medtronic –y no contra el médico- conforme a las reglas de responsabilidad civil objetiva y por negligencia del Common Law neoyorquino. Sin embargo, el Tribunal Supremo federal de los EE.UU., en ponencia del Magistrado Antonin Gregory Scalia, votó, por mayoría de ocho magistrados, rechazar el recurso de la Sra. Riegel y confirmar la sentencia de segunda instancia, desestimatoria de la demanda, porque consideró que la regla de primacía del derecho regulatorio federal sobre seguridad de productos sanitarios [Medical Device Amendments de 1976, 21 U.S.C. Artículo 360k(a)] excluye la aplicabilidad no sólo del derecho regulatorio estatal sobre seguridad de productos sanitarios, sino también del Common Law sobre responsabilidad civil del fabricante.

Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models

Background: Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results: Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions: Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.

An efficient solver for weighted Max-SAT

We present a new branch and bound algorithm for weighted Max-SAT, called Lazy which incorporates original data structures and inference rules, as well as a lower bound of better quality. We provide experimental evidence that our solver is very competitive and outperforms some of the best performing Max-SAT and weighted Max-SAT solvers on a wide range of instances.

Soybean (Glycine max. L.) and bacteroid glyoxylate cycle activities during nodular senescence.

Soybean (Glycine max. L.) nodular senescence results in the dismantling of the peribacteroid membrane (PBM) and in an increase of soybean isocitrate lyase (ICL; EC 4.1.3.1) and malate synthase (MS; EC 4.1.3.2) mRNA and protein levels. This suggests that in senescing soybean nodular cells, the specific glyoxylate cycle enzyme activities might be induced to reallocate carbon obtained from the PBM degradation. In order to evaluate as well the carbon metabolism of the nitrogen-fixing Bradyrhizobium japonicum endosymbiotic bacteroids during nodular senescence, their glyoxylate cycle activities were also investigated. To this end, partial DNA sequences were isolated from their icl and ms genes, but the corresponding mRNAs were not detected in the microorganisms. It was also observed that the bacteroid ICL and MS activities were negligible during nodular senescence. This suggests that glyoxylate cycle activities are not reinitiated in the bacteroids under these physiological conditions. In case the microorganisms nevertheless feed on the PBM degradation products, this might occur via the citric acid cycle exclusively.

An overview of the metabolic differences between Bradyrhizobium japonicum 110 bacteria and differentiated bacteroids from soybean (Glycine max) root nodules: An in vitro 13C-and 31P-nuclear magnetic resonance spectroscopy study

Bradyrhizobium japonicum is a symbiotic nitrogen-fixing soil bacteria that induce root nodules formation in legume soybean (Glycine max.). Using 13C- and 31P-nuclear magnetic resonance (NMR) spectroscopy, we have analysed the metabolite profiles of cultivated B.japonicum cells and bacteroids isolated from soybean nodules. Our results revealed some quantitative and qualitative differences between the metabolite profiles of bacteroids and their vegetative state. This includes in bacteroids a huge accumulation of soluble carbohydrates such as trehalose, glutamate, myo-inositol and homospermidine as well as Pi, nucleotide pools and intermediates of the primary carbon metabolism. Using this novel approach, these data show that most of the compounds detected in bacteroids reflect the metabolic adaptation of rhizobia to the surrounding microenvironment with its host plant cells.