Sentence examples for model bacterial and from inspiring English sources

Atomistic molecular dynamics simulations have been used to investigate the mode of interaction of B2088 with model bacterial and mammalian membranes.

To address this, we compared the biomembrane interactions of host defense peptide IDR-1010cys (1) in free form, (2) as a soluble polymer conjugate, and (3) with one end tethered to a solid support with model bacterial and mammalian lipid membranes.

This issue has been brought to the forefront recently by experimental work on group-beneficial traits in model bacterial and yeast systems [6], [9] [20] including, but not limited to, work using Staphylococcus aureus, Pseudomonas fluorescens, Pseudomonas aeruginosa, Myxococcus xanthus, Saccharomyces cerevisiae and Escherichia coli.

For model bacterial and viral pathogens, sensitivity in 10% human serum was found to be 10 bacterial cells/mL and 10 virus particles/mL, consistent with clinical utility.

Here, we demonstrate the detection of model bacterial and viral pathogens, Escherichia coli and MS2 virus at 10 bacterial cells/mL and 10 virions/mL, respectively, using suspended, microfabricated retroreflector cubes as optical labels conjugated to antibodies.

Advances in biofilm biology have been made over decades for model bacterial species, and include characterizations of social behaviors and cellular differentiation during biofilm development.

Thus, the peptides are shown to have the ability to form a helical structure, to bind to model bacterial membranes and permeabilize model liposomes.

Salmonella enterica (S. enterica) is frequently used as a model bacterial pathogen and therefore its proteome has already been intensively studied.

Those previous suggestions were based on model bacterial pathways and the presence of genes on the metagenome.

This weaponized composite molecule (Pentobra) induced membrane-destabilizing negative Gaussian curvature in model bacterial membranes and permeabilized E. coli cell inner membranes.

In the present study we used bacterial species sensitivity distributions derived from a comprehensive set of minimum inhibitory concentration (MIC) distributions of antibiotics to model bacterial sensitivities and characterize the selective pressure that antibiotic pollution may exert on bacteria of importance to public health that are found in the environment.