The Influence of Antimicrobial Peptides and Mucolytics on the Integrity of Biofilms Consisting of Bacteria and Yeasts as Affecting Voice Prosthetic Air Flow Resistances

The integrity of biofilms on voice prostheses used to rehabilitate speech in laryngectomized patients causes unwanted increases in airflow resistance, impeding speech. Biofilm integrity is ensured by extracellular polymeric substances (EPS). This study aimed to determine whether synthetic salivary peptides or mucolytics, including N-acetylcysteine and ascorbic acid, influence the integrity of voice prosthetic biofilms. Biofilms were grown on voice prostheses in an artificial throat model and exposed to synthetic salivary peptides, mucolytics and two different antiseptics (chlorhexidine and Triclosan). Synthetic salivary peptides did not reduce the air flow resistance of voice prostheses after biofilm formation. Although both chlorhexidine and Triclosan reduced microbial numbers on the prostheses, only the Triclosan-containing positive control reduced the air flow resistance. Unlike ascorbic acid, the mucolytic N-acetylcysteine removed most EPS from the biofilms and induced a decrease in air flow resistance.     

Improved tests for heterogeneity across a region of DNA sequence in the ratio of polymorphism to divergence

The neutral theory of molecular evolution predicts that the ratio of polymorphisms to fixed differences should be fairly uniform across a region of DNA sequence. Significant heterogeneity in this ratio can indicate the effects of balancing selection, selective sweeps, mildly deleterious mutations, or background selection. Comparing an observed heterogeneity statistic with simulations of the heterogeneity resulting from random phylogenetic and sampling variation provides a test of the statistical significance of the observed pattern. When simulated data sets containing heterogeneity in the polymorphism-to-divergence ratio are examined, different statistics are most powerful for detecting different patterns of heterogeneity. The number of runs is most powerful for detecting patterns containing several peaks of polymorphism; the Kolmogorov-Smirnov statistic is most powerful for detecting patterns in which one end of the gene has high polymorphism and the other end has low polymorphism; and a newly developed statistic, the mean sliding G statistic, is most powerful for detecting patterns containing one or two peaks of polymorphism with reduced polymorphism on either side. Nine out of 27 genes from the Drosophila melanogaster subgroup exhibit heterogeneity that is significant under at least one of these three tests, with five of the nine remaining significant after a correction for multiple comparisons, suggesting that detectable evidence for the effects of some kind of selection is fairly common.      

Detecting non-neutral heterogeneity across a region of DNA sequence in the ratio of polymorphism to divergence

Natural selection, in the form of balancing selection or selective sweeps, can result in a decoupling of the amounts of molecular polymorphism and divergence. Thus natural selection can cause some areas of DNA sequence to have greater silent polymorphism, relative to divergence between species, than other areas. It would be useful to have a statistical test for heterogeneity in the polymorphism to divergence ratio across a region of DNA sequence, one that could identify heterogeneity greater than that expected from the neutral processes of mutation, drift, and recombination. The only currently available test requires that a region be arbitrarily divided into sections that are compared with each other, and the subjectivity of this division could be problematic. Here a test is proposed in which runs of polymorphic and fixed sites are counted, where a "run" is a set of one or more sites of one type preceded and followed by the other type. The number of runs is smaller than otherwise expected if polymorphisms are clumped together. By simulating neutral evolution and comparing the observed number of runs to the simulations, a statistical test is possible which does not require any a priori decisions about subdivision.      

Molecular docking analysis of flavonoids with aldose reductase

Diabetes mellitus is a group of metabolic disorders that has risen to become the third most common cause in humans in recent years. The development of new bioactive substances from natural sources is a relatively new area. Flavonoids are believed to have a variety of beneficial properties in nature, including anti-inflammatory, antimicrobial, anticancer, antioxidant, neuroprotective, and anti-HIV properties. 15 naturally occurring flavonoids docked with the selected target aldose reductase. We report the optimal binding of Acumitin, Agathisflavone, Agehoustin B, and alpha-Toxicarol with aldose reductase for further consideration in drug discovery for T2DM.