Uniform Semiclassical Wavepacket Propagation and Eigenstate Extraction in a Smooth Chaotic System

A uniform semiclassical propagator is used to time evolve a wavepacket in a smooth Hamiltonian system at energies for which the underlying classical motion is chaotic. The propagated wavepacket is Fourier transformed to yield a scarred eigenstate.Comment: Postscript file is tar-compressed and uuencoded (342K); postscript file produced is 1216

Signatures of Classical Periodic Orbits on a Smooth Quantum System

Gutzwiller's trace formula and Bogomolny's formula are applied to a non--specific, non--scalable Hamiltonian system, a two--dimensional anharmonic oscillator. These semiclassical theories reproduce well the exact quantal results over a large spatial and energy range.Comment: 12 pages, uuencoded postscript file (1526 kb

Persistence of porcine reproductive and respiratory syndrome virus and porcine circovirus type 2 in bacterial biofilms

The aim of this pilot project was to investigate association of viruses with bacterial biofilms. Our preliminary data indicate that important viral pathogens of swine, namely, porcine reproductive and respiratory syndrome virus and porcine circovirus type 2, can associate with and persist within bacterial biofilms for several days

Altering the primacy bias – How does a prior task affect mismatch negativity (MMN)?

The role in which two tones are first encountered in an unattended oddball sequence affects how deviance detection, reflected by mismatch negativity (MMN), treats them later when the roles reverse: a “primacy bias”. We tested whether this effect is modulated by previous behavioural relevance assigned to the two tones. To this end, sequences in which the roles of the two tones alternated were preceded by a go-nogo task in which tones were presented with equal probability. Half of the participants were asked to respond to the short sounds, the other half to long sounds. Primacy bias was initially abolished but returned dependent upon the gostimulus the participant was assigned. Results demonstrate a long-term impact of prior learning on deviance detection; and that even when prior importance/equivalence is learned, the bias ultimately returns. Results are discussed in terms of persistent go-stimulus-specific changes in responsiveness to sound

A role for lipid rafts in the protection afforded by docosahexaenoic acid against ethanol toxicity in primary rat hepatocytes.

International audience: Previously, we demonstrated that eicosapentaenoic acid enhanced ethanol-induced oxidative stress and cell death in primary rat hepatocytes via an increase in membrane fluidity and lipid raft clustering. In this context, another n-3 polyunsaturated fatty acid, docosahexaenoic acid (DHA), was tested with a special emphasis on physical and chemical alteration of lipid rafts. Pretreatment of hepatocytes with DHA reduced significantly ethanol-induced oxidative stress and cell death. DHA protection could be related to an alteration of lipid rafts. Indeed, rafts exhibited a marked increase in membrane fluidity and packing defects leading to the exclusion of a raft protein marker, flotillin. Furthermore, DHA strongly inhibited disulfide bridge formation, even in control cells, thus suggesting a disruption of protein-protein interactions inside lipid rafts. This particular spatial organization of lipid rafts due to DHA subsequently prevented the ethanol-induced lipid raft clustering. Such a prevention was then responsible for the inhibition of phospholipase C-γ translocation into rafts, and consequently of both lysosome accumulation and elevation in cellular low-molecular-weight iron content, a prooxidant factor. In total, the present study suggests that DHA supplementation could represent a new preventive approach for patients with alcoholic liver disease based upon modulation of the membrane structures

Moving biochemistry and molecular biology courses online in times of disruption: Recommended practices and resources ‐ a collaboration with the faculty community and ASBMB

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163423/2/bmb21354_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163423/1/bmb21354.pd

Random sampling of elementary flux modes in large-scale metabolic networks

Motivation: The description of a metabolic network in terms of elementary (flux) modes (EMs) provides an important framework for metabolic pathway analysis. However, their application to large networks has been hampered by the combinatorial explosion in the number of modes. In this work, we develop a method for generating random samples of EMs without computing the whole set. Results: Our algorithm is an adaptation of the canonical basis approach, where we add an additional filtering step which, at each iteration, selects a random subset of the new combinations of modes. In order to obtain an unbiased sample, all candidates are assigned the same probability of getting selected. This approach avoids the exponential growth of the number of modes during computation, thus generating a random sample of the complete set of EMs within reasonable time. We generated samples of different sizes for a metabolic network of Escherichia coli, and observed that they preserve several properties of the full EM set. It is also shown that EM sampling can be used for rational strain design. A well distributed sample, that is representative of the complete set of EMs, should be suitable to most EM-based methods for analysis and optimization of metabolic networks