Penetratin is a 16-residue peptide ] derived from the Antennapedia homeodomain, which is used as a vector for cellular internalization of hydrophilic molecules. In order to unravel the membrane translocation mechanism, we synthesized new penetratin variants. The contribution of the positively charged residues was studied by double substitutions of Lys and/or Arg residues to Ala, while the specific contribution of Trp48 and Trp56 was studied by individual substitution of these residues to Phe. Trp fluorescence titrations demonstrated the importance of the positively charged residues for the initial electrostatic interaction of the peptide with negatively charged vesicles. In contrast, none of the Trp residues seemed critical for this initial interaction. Trp fluorescence quenching experiments showed that penetratin lies close to the water-lipid interface in a tilted orientation, while circular dichroism indicated that lipid binding increased the a-helical structure of the peptides. The R53A/K57A and R52A/ K55A substitutions increased calcein leakage and decreased vesicle aggregation compared to wild-type penetratin. These variants insert deeper into the lipid bilayer, due to an increased hydrophobic environment of Trp56. The W48F and W56F substitutions had a minor effect on membrane insertion and destabilization. Cellular internalization of the R53A/K57A, R52A/K55A and K46A/K57A variants by MDCK cells was similar to wild-type penetratin, as shown by flow cytometry. Moreover, residue Trp48 specifically contributed to endocytosis-independent internalization by MDCK cells, as demonstrated by the lower uptake of the W48F variant compared to wild-type penetratin and to the W56F variant. None of the penetratin variants was haemolytic or cytotoxic.Keywords: penetratin; Antennapedia homeodomain; lipid vesicles; membrane; cellular internalization.Homeoproteins are a class of well-conserved transcription factors, involved in multiple morphological processes [1,2]. The 60-residue DNA-binding homeodomain of the Drosophila Antennapedia homeoprotein was shown to internalize into cells via a receptor-independent mechanism [3][4][5]. This homeodomain consists of three helices and a loop separating helix 2 and 3 [2]. Mutagenesis experiments demonstrated that the third helix drives the homeodomain internalization [6]. The short 16-residue penetratin peptide, corresponding to residues RQIKIWFQNRRMK WKK(43-58) of helix 3, is able to translocate through the plasma membrane to the cytosol and nucleus of living cells, both at 37°C and 4°C.Translocation of the penetratin peptide occurs even when it is coupled to hydrophilic molecules (e.g. phosphopeptides, oligonucleotides, peptidic nucleic acids, drugs, etc.) [7][8][9][10][11][12][13][14][15][16]. The penetratin peptide is therefore considered as a member of the so-called ÔTrojanÕ peptides or cell-penetrating peptides (CPP) that are water-soluble peptides with a low lytic activity that can be used as vectors for cellular internalization of hydrophilic biomolecules and drugs [17,18]. De...

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This study evaluates the most popular recommender system algorithms for use on both sides of the labor market: job recommendation and job seeker recommendation. Recent research shows the drawbacks of focusing solely on predictive power when evaluating recommender systems, which become especially prominent in job-and job seeker recommendation, where aspects such as reciprocity and item spread are two other vital performance metrics for the quality of recommendations. Besides evaluating using these extra metrics, we compare recommendation with search using free text search engines. We measure what is gained, and what is lost when consuming items (jobs and job seekers) retrieved using search versus items presented via a recommender system. Based on insights in date recommendation literature, we propose changes to rating matrix construction aimed at mitigating the drawbacks of recommendation in the labor market. Our results, obtained from extensive experimentation on three datasets gathered from the Flemish public employment services, show that popular recommender algorithms perform significantly worse than user search in terms of reciprocity. Furthermore, we show that by swapping the rating matrices between two sides of a reciprocal recommender context, we can outperform user search in terms of reciprocity with limited trade off in predictive power. The insights from this research can help actors in the labor market to better understand the positioning of recommendation versus search, and to provide better job recommendations and job seeker recommendations.

Microblogging websites such as Twitter have caused sentiment analysis research to increase in popularity over the last several decades. However, most studies focus on the English language, which leaves other languages underrepresented. Therefore, in this paper, we compare several modeling techniques for sentiment analysis using a new dataset containing Flemish tweets. The key contribution of our paper lies in its innovative experimental design: we compared different preprocessing techniques and vector representations to find the best-performing combination for a Flemish dataset. We compared models belonging to four different categories: lexicon-based methods, traditional machine-learning models, neural networks, and attention-based models. We found that more preprocessing leads to better results, but the best-performing vector representation approach depends on the model applied. Moreover, an immense gap was observed between the performances of the lexicon-based approaches and those of the other models. The traditional machine learning approaches and the neural networks produced similar results, but the attention-based model was the best-performing technique. Nevertheless, a tradeoff should be made between computational expenses and performance gains.

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