Free-standing biomimetic polymer membrane imaged with atomic force microscopy

Fluid polymeric biomimetic membranes are probed with atomic force microscopy (AFM) using probes with both normal tetrahedrally shaped tips and nanoneedle-shaped Ag(2)Ga rods. When using nanoneedle probes, the collected force volume data show three distinct membrane regions which match the expected membrane structure when spanning an aperture in a hydrophobic scaffold. The method used provides a general method for mapping attractive fluid surfaces. In particular, the nanoneedle probing allows for characterization of free-standing biomimetic membranes with thickness on the nanometer scale suspended over 300-μm-wide apertures, where the membranes are stable toward hundreds of nanoindentations without breakage.     

Effect of glycine substitution on Fmoc-diphenylalanine self-assembly and gelation properties

We have investigated the self-assembly behavior of fluorenyl-9-methoxycarbonyl (Fmoc)-FG, Fmoc-GG, and Fmoc-GF and compared it to that of Fmoc-FF using potentiometry, fluorescence and infrared spectroscopy, transmission electron microscopy, wide-angle X-ray scattering, and oscillatory rheometry. Titration experiments revealed a substantially shifted apparent pK(a) transition for Fmoc-FG, Fmoc-GG, and Fmoc-GF. The apparent pK(a) values observed correlated with the hydrophobicity (log P) of the Fmoc-dipeptide molecules. Fmoc-GG and Fmoc-GF were found to self-assemble only in their protonated form (below their apparent pK(a)), while Fmoc-FG formed self-assembled structures above and below its apparent pK(a). Fmoc-GG and Fmoc-FG were found to form hydrogels below their apparent pK(a) transitions in agreement with the entangled fibers morphologies revealed by TEM. Unlike Fmoc-FF and Fmoc-GG, Fmoc-FG showed unusual gelation behavior as gels were found to form upon heating. Fmoc-GF formed precipitates instead of a hydrogel below its apparent pK(a) in agreement with the formation of micrometer scale sheetlike structures observed by TEM. The fact that all four Fmoc-dipeptides were found to self-assemble suggests that the main driving force behind the self-assembly process is a combination of the hydrophobic and π-π interactions of the fluorenyl moieties with a secondary role for hydrogen bonding of the peptidic components. The nature of the peptidic tail was found to have a pronounced effect on the type of self-assembled structure formed. This work indicates that the substitution of phenylalanine by glycine significantly impacts on the mode of assembly and illustrates the versatility of aromatic peptide amphiphiles in the formation of structurally diverse nanostructures.     

Biomimetic membrane arrays on cast hydrogel supports

Lipid bilayers are intrinsically fragile and require mechanical support in technical applications based on biomimetic membranes. Tethering the lipid bilayer membranes to solid substrates, either directly through covalent or ionic substrate-lipid links or indirectly on substrate-supported cushions, provides mechanical support but at the cost of small molecule transport through the membrane-support sandwich. To stabilize biomimetic membranes while allowing transport through a membrane-support sandwich, we have investigated the feasibility of using an ethylene tetrafluoroethylene (ETFE)/hydrogel sandwich as the support. The sandwich is realized as a perforated surface-treated ETFE film onto which a hydrogel composite support structure is cast. We report a simple method to prepare arrays of lipid bilayer membranes with low intrinsic electrical conductance on the highly permeable, self-supporting ETFE/hydrogel sandwiches. We demonstrate how the ETFE/hydrogel sandwich support promotes rapid self-thinning of lipid bilayers suitable for hosting membrane-spanning proteins.     

Modeling of one-dimensional smoldering of polyurethane in microgravity conditions

Results are presented from a model of forward smoldering combustion of polyurethane foam in microgravity. The transient one-dimensional numerical-model is based on that developed at the University of Texas at Austin. The conservation equations of energy, species, and mass in the porous solid and in the gas phases are numerically solved. The solid and the gas phases are not assumed to be in thermal or in chemical equilibrium. The chemical reactions modeled consist of foam oxidation and pyrolysis reactions, as well as char oxidation. The model has been modified to account for new polyurethane kinetics parameters and radial heat losses to the surrounding environment. The kinetics parameters are extracted from thermogravimetric analyses published in the literature and using Genetic Algorithms as the optimization technique. The model results are compared with previous tests of forward smoldering combustion in microgravity conducted aboard the NASA Space Shuttle. The model calculates well the propagation velocities and the overall smoldering characteristics. Direct comparison of the solution with the experimental temperature profiles shows that the model predicts well these profiles at high temperature, but not as well at lower temperatures. The effect of inlet gas velocity is examined, and the minimum airflow for ignition is identified. It is remarkable that this one-dimensional model with simplified kinetics is capable of predicting cases of smolder ignition but with no self-propagation away from the igniter region. The model is used for better understanding of the controlling mechanisms of smolder combustion for the purpose of fire safety, both in microgravity and normal gravity, and to extend the unique microgravity data to wider conditions avoiding the high cost of space-based experiments.     

Chiral symmetry breaking and meson decays in a relativistic quark model

Applying two different Lorentz-covariant quark models, one of them being essentially nonrelativistic, chiral symmetry breaking parameters of strong interaction will be calculated. Also attention will be paid to meson decays. The model retaining relativistic spinor structure for quark-antiquark wave functions turns out to be more appropriate than the nonrelativistic one.     

Molecular geometries and moments from the maximum overlap criterion

The maximized overlap population, defined as Σ_μ≠νP_μνS_μν, and a related quantity, Σ_μ,νP_μνS²_μν are computed for a series of configurations. The extremum of both approximate molecular geometries, the latter with an accuracy suitable for predictive value. The maximum overlap orbitals predict dipole and quadrupole moments that give reasonable agreement with experimental values.     

Determination of submicromolar amounts of uranium(VI) by compleximetric titration with pyridine-2,6-dicarboxylic acid

Uranium(VI) is selectively determined by a compleximetric titration with pyridine-2,6-dicarboxylic acid, using arsenazo-I indicator and hexamethylenetetramine buffer at pH 4.9. Cyclohexanediaminetetraacetic acid and diethylenetriaminepentaacetic acid provide masking of interfering metal ions. A probe colorimeter apparatus is recommended for end-point detection. The relative standard deviation is 0.6% for 0.17–0.76 μmol of uranium.     

Green's-function reaction dynamics: a particle-based approach for simulating biochemical networks in time and space

We have developed a new numerical technique, called Green's-function reaction dynamics (GFRD), that makes it possible to simulate biochemical networks at the particle level and in both time and space. In this scheme, a maximum time step is chosen such that only single particles or pairs of particles have to be considered. For these particles, the Smoluchowski equation can be solved analytically using Green's functions. The main idea of GFRD is to exploit the exact solution of the Smoluchoswki equation to set up an event-driven algorithm, which combines in one step the propagation of the particles in space with the reactions between them. The event-driven nature allows GFRD to make large jumps in time and space when the particles are far apart from each other. Here, we apply the technique to a simple model of gene expression. The simulations reveal that spatial fluctuations can be a major source of noise in biochemical networks. The calculations also show that GFRD is highly efficient. Under biologically relevant conditions, GFRD is up to five orders of magnitude faster than conventional particle-based techniques for simulating biochemical networks in time and space. GFRD is not limited to biochemical networks. It can also be applied to a large number of other reaction-diffusion problems.