Characterization and Biological Activities of Ocellatin Peptides from the Skin Secretion of the Frog Leptodactylus pustulatus

Eight new peptides were isolated from the skin secretion of the frog Leptodactylus pustulatus and their amino acid sequences determined by de novo sequencing and by cDNA cloning. Structural similarities between them and other antimicrobial peptides from the skin secretion of Leptodactylus genus frogs were found. Ocellatins-PT1 to -PT5 (25 amino acid residues) are amidated at the C-terminus, while ocellatins-PT6 to -PT8 (32 amino acid residues) have free carboxylates. Antimicrobial activity, hemolytic tests, and cytotoxicity against a murine fibroblast cell line were investigated. All peptides, except for ocellatin-PT2, have antimicrobial activity against at least one Gram negative strain. Ocellatin-PT8 inhibited the growth of Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, and Salmonella choleraesuis strains with MICs in the 60−240 μM range. No significant effect was observed in human erythrocytes and in a murine fibroblast cell line after exposure to the peptides at MICs. A comparison between sequences obtained by both direct HPLC-MS de novo sequencing and cDNA cloning demonstrates the secretion of mature peptides derived from a pre-pro-peptide structure.

An automatic voice pleasantness classification system based on prosodic and acoustic patterns of voice preference

In the last few years the number of systems and devices that use voice based interaction has grown significantly. For a continued use of these systems the interface must be reliable and pleasant in order to provide an optimal user experience. However there are currently very few studies that try to evaluate how good is a voice when the application is a speech based interface. In this paper we present a new automatic voice pleasantness classification system based on prosodic and acoustic patterns of voice preference. Our study is based on a multi-language database composed by female voices. In the objective performance evaluation the system achieved a 7.3% error rate.