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Most of us receive numerous spam e-mails, texts that in one or the other way try to convince us to engage in the transaction of enormous sums of money, promising enormous benefits. In reality, such scam e-mails are fraudulent attempts to swindle money from unsuspecting Internet users. Language, its social contexts, and the composition of texts play a crucial role in the scammers’ strategies to approach their victims. This article uncovers and discusses some of the linguistic strategies by which scammers try to shape a sense of identity and mutual relationship – in the face of virtual anonymity –, and to involve their readers personally. In their attempts to get the recipients involved, scammers combine cultural indexicals, interactional roles, and narrative strategies. The analysis distinguishes three different narrative strategies in scam e-mails: Based on first, second, and third person stories, scammers establish links with the recipients by combining fictional content with real-world contexts. Some of the narratives display quite elaborate and artful traits and involve prototypical functions of traditional fairy tales. Hereby they implicitly connect the story content with the interactional roles of e-mail communication.
We performed a bioinformatical analysis of protein export elements (PEXEL) in the putative proteome of the malaria parasite Plasmodium falciparum. A protein family-specific conservation of physicochemical residue profiles was found for PEXEL-flanking sequence regions. We demonstrate that the family members can be clustered based on the flanking regions only and display characteristic hydrophobicity patterns. This raises the possibility that the flanking regions may contain additional information for a family-specific role of PEXEL. We further show that signal peptide cleavage results in a positional alignment of PEXEL from both proteins with, and without, a signal peptide.
Experimental results are presented for 180 in silico designed octapeptide sequences and their stabilizing effects on the major histocompatibility class I molecule H-2Kb. Peptide sequence design was accomplished by a combination of an ant colony optimization algorithm with artificial neural network classifiers. Experimental tests yielded nine H-2Kb stabilizing and 171 nonstabilizing peptides. 28 among the nonstabilizing octapeptides contain canonical motif residues known to be favorable for MHC I stabilization. For characterization of the area covered by stabilizing and non-stabilizing octapeptides in sequence space, we visualized the distribution of 100,603 octapeptides using a self-organizing map. The experimental results present evidence that the canonical sequence motives of the SYFPEITHI database on their own are insufficient for predicting MHC I protein stabilization.