Peptide Tyrosine Arginine, a potent immunomodulatory peptide isolated and structurally characterized from the skin secretions of the dusky gopher frog, Rana sevosa

An octadecapeptide was isolated from the skin secretions of the dusky gopher frog (Rana sevosa) on the basis of histamine release from rat peritoneal mast cells. This peptide was purified to homogeneity by HPLC and found to have the following primary structure, YLKGCWTKSYPPKPCFSR, using both Edman degradation chemistry and peptide sequencing using high-resolution mass spectrometry (Q-TOF MS). The peptide, named peptide Tyrosine Arginine (pYR) shares 77.8% homology with peptide Leucine Arginine (pLR). The effects of the natural amidated peptide, non-amidated peptide and C-loop region of pYR on granulopoiesis and neutrophil apoptosis were investigated. All three analogues inhibited the early development of granulocyte macrophage colonies from bone marrow stem cells but did not induce apoptosis of the end stage granulocytes, the mature neutrophil. Thus, pYR is a novel member of an important and emerging new class of amphibian peptides with hemopoietic actions. (c) 2004 Elsevier Inc. All rights reserved.

ASR emotional speech: Clarifying the issues and enhancing performance

There are multiple reasons to expect that recognising the verbal content of emotional speech will be a difficult problem, and recognition rates reported in the literature are in fact low. Including information about prosody improves recognition rate for emotions simulated by actors, but its relevance to the freer patterns of spontaneous speech is unproven. This paper shows that recognition rate for spontaneous emotionally coloured speech can be improved by using a language model based on increased representation of emotional utterances. The models are derived by adapting an already existing corpus, the British National Corpus (BNC). An emotional lexicon is used to identify emotionally coloured words, and sentences containing these words are recombined with the BNC to form a corpus with a raised proportion of emotional material. Using a language model based on that technique improves recognition rate by about 20%. (c) 2005 Elsevier Ltd. All rights reserved.