The yeast Metschnikowia reukaufii is a natural contaminant of nectar and is vectored to the flowers of the field milkweed Asclepias syriaca by insects, some of which are pollinators of the plants. In its natural habitat, the yeast inhibits the germination of the milkweed's pollen, which normally uses nectar in the stigmatic cavity for germination. This inhibition is irreversible after about 8 h of exposure to the yeasts. Two selected strains of the yeast were isolated and investigated for their effects on pollen germination in vitro. The two strains, and their mixture, affected pollen germination adversely by reducing its amount and vigour and causing any pollen tubes that were produced to burst: One strain was more virulent than the other, and the mixture seemed to have an additive effect. The strains may be more efficacious than the natural assemblage of microbes in disrupting fertilization of milkweed flowers because they cause the immediate death (bursting) of the growing microgametophyte (pollen and tube). Key words: yeasts, pollen germination, milkweed, Metschnikowia reukaufii, Asclepias syriaca.

We present the direct synthesis of stabilizer-free Cu–Ir alloy nanoparticles (NPs) with tunable compositions. Cu and Ir are classically immiscible in the bulk. Therefore, the physical and catalytic properties of Cu–Ir alloys are largely unknown. A convenient microwave-assisted method utilizes readily available Cu2+ salts and IrCl3 in a modified polyol reaction; NaOH facilitates rapid solvent-assisted coreduction to yield Cu x Ir(100–x)NPs, where x can be varied within the approximate range 10–50. The as-synthesized NPs form stable dispersions of small (∼2 nm) and near-monodisperse cuboctahedra without the requirement of organic stabilizing (capping) agents, resulting in nanostructures that are directly amenable to heterogeneous catalysis. Cu x Ir(100–x)NPs supported on mesoporous Co3O4 show high selectivity toward the selective partial hydrogenation of crotonaldehyde to yield >40% crotyl alcohol in the vapor phase. The selectivity toward CO versus CC bond hydrogenation is largely insensitive to the Cu:Ir ratio but more Ir rich compositions are also more highly active. Density functional theory (DFT) studies explain this behavior in two ways: first the Co3O4 support enhances selective CO bond activation of the crotonaldehyde feedstock via favorable support-reagent adsorption; second, increasingly Ir-rich CuIrNP surfaces provide more Ir- sites, resulting in higher hydrogenation activity.

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Molecular crowding occurs when the total concentration of macromolecular species in a solution is so high that a considerable proportion of the volume is physically occupied and therefore not accessible to other molecules. This results in significant changes in the solution properties of the molecules in such systems. Macromolecular crowding is ubiquitous in biological systems due to the generally high intracellular protein concentrations. The major hindrance to understanding crowding is the lack of direct comparison of experimental data with theoretical or simulated data. Self-diffusion is sensitive to changes in the molecular weight and shape of the diffusing species, and the available diffusion space (i.e., diffusive obstruction). Consequently, diffusion measurements are a direct means for probing crowded systems including the self-association of molecules. In this work, nuclear magnetic resonance (NMR) measurements of the self-diffusion of four amino acids (glycine, alanine, valine and phenylalanine) up to their solubility limit in water were compared directly with molecular dynamics simulations. The experimental data were then analyzed using various models of aggregation and obstruction. Both experimental and simulated data revealed that the diffusion of both water and the amino acids were sensitive to the amino acid concentration. The direct comparison of the simulated and experimental data afforded greater insights into the aggregation and obstruction properties of each amino acid.

NMR diffusion measurements have proven to be a very powerful technique for probing the solution dynamics of polymer systems. In theory, it is possible to extract a range of useful information including molecular weights from the diffusion data. In practice, especially outside the infinite dilution regime, the data analysis is further complicated by numerous effects including macroscopic and microscopic averaging. Here the averaging effects in dilute bimodal narrow molecular weight poly(methyl methacrylate) in deuterated chloroform solutions are studied at 298 K and cogent models developed to analyze the data. Simulations are performed which represent different limits of diffusive behavior in bimodal solutions and the suitability of the simulations are found to be dependent on the ratio of the molecular weights in the solution.