Highly Selective End-Tagged Antimicrobial Peptides Derived from PRELP

Background: Antimicrobial peptides (AMPs) are receiving increasing attention due to resistance development against conventional antibiotics. Pseudomonas aeruginosa and Staphylococcus aureus are two major pathogens involved in an array of infections such as ocular infections, cystic fibrosis, wound and post-surgery infections, and sepsis. The goal of the study was to design novel AMPs against these pathogens. Methodology and Principal Findings: Antibacterial activity was determined by radial diffusion, viable count, and minimal inhibitory concentration assays, while toxicity was evaluated by hemolysis and effects on human epithelial cells. Liposome and fluorescence studies provided mechanistic information. Protease sensitivity was evaluated after subjection to human leukocyte elastase, staphylococcal aureolysin and V8 proteinase, as well as P. aeruginosa elastase. Highly active peptides were evaluated in ex vivo skin infection models. C-terminal end-tagging by W and F amino acid residues increased antimicrobial potency of the peptide sequences GRRPRPRPRP and RRPRPRPRP, derived from proline arginine-rich and leucine-rich repeat protein (PRELP). The optimized peptides were antimicrobial against a range of Gram-positive S. aureus and Gram-negative P. aeruginosa clinical isolates, also in the presence of human plasma and blood. Simultaneously, they showed low toxicity against mammalian cells. Particularly W-tagged peptides displayed stability against P. aeruginosa elastase, and S. aureus V8 proteinase and aureolysin, and the peptide RRPRPRPRPWWWW-NH2 was effective against various "superbugs'' including vancomycin-resistant enterococci, multi-drug resistant P. aeruginosa, and methicillin-resistant S. aureus, as well as demonstrated efficiency in an ex vivo skin wound model of S. aureus and P. aeruginosa infection. Conclusions/Significance: Hydrophobic C-terminal end-tagging of the cationic sequence RRPRPRPRP generates highly selective AMPs with potent activity against multiresistant bacteria and efficiency in ex vivo wound infection models. A precise "tuning'' of toxicity and proteolytic stability may be achieved by changing tag-length and adding W-or F-amino acid tags

Online unit covering in Euclidean space

We revisit the online Unit Covering problem in higher dimensions: Given a set of n points in Rd, that arrive one by one, cover the points by balls of unit radius, so as to minimize the number of balls used. In this paper, we work in R d using Euclidean distance. The current best competitive ratio of an online algorithm, O(2 d d log d), is due to Charikar et al. (2004); their algorithm is deterministic. (I) We give an online deterministic algorithm with competitive ratio O(1.321 d ), thereby improving on the earlier record by an exponential factor. In particular, the competitive ratios are 5 for the plane and 12 for 3-space (the previous ratios were 7 and 21, respectively). For d = 3, the ratio of our online algorithm matches the ratio of the current best offline algorithm for the same problem due to Biniaz et al. (2017), which is remarkable (and rather unusual). (II) We show that the competitive ratio of every deterministic online algorithm (with an adaptive deterministic adversary) for Unit Covering in Rd under the L 2 norm is at least d + 1 for every d ≥ 1. This greatly improves upon the previous best lower bound, Ω(log d/ log log log d), due to Charikar et al. (2004). (III) We obtain lower bounds of 4 and 5 for the competitive ratio of any deterministic algorithm for online Unit Covering in R 2 and respectively R 3 ; the previous best lower bounds were both 3. (IV) When the input points are taken from the square or hexagonal lattices in R 2 , we give deterministic online algorithms for Unit Covering with an optimal competitive ratio of 3

Corporate Governance and Board Effectiveness in Maritime Firms

This paper examines the financial performance effect of three corporate governance mechanisms: (i) founding family CEO, (ii) board ownership, and (iii) board independence. The developed hypotheses are tested using multivariate ordinary least-squares regression on a 3-year sample of 32 publicly traded maritime firms from Norway and Sweden, and compared to the results of the same hypotheses tested on a sample of 96 manufacturing firms. This study concludes that maritime firms with a founding family CEO have better financial performance than maritime firms with a non-founding family CEO. Support was also found for the hypothesis that a high level of board independence enhances profitability in maritime firms. Contrary to agency theory predictions, no significant relation was found between the level of board ownership and firm profitability in maritime firms, although board ownership control was significant in the sample of manufacturing firms. Maritime Economics & Logistics (2003) 5, 40–54. doi:10.1057/palgrave.mel.9100059

A text-mining analysis of the human phenome

Contains fulltext : 36178.pdf (publisher's version ) (Closed access)A number of large-scale efforts are underway to define the relationships between genes and proteins in various species. But, few attempts have been made to systematically classify all such relationships at the phenotype level. Also, it is unknown whether such a phenotype map would carry biologically meaningful information. We have used text mining to classify over 5000 human phenotypes contained in the Online Mendelian Inheritance in Man database. We find that similarity between phenotypes reflects biological modules of interacting functionally related genes. These similarities are positively correlated with a number of measures of gene function, including relatedness at the level of protein sequence, protein motifs, functional annotation, and direct protein-protein interaction. Phenotype grouping reflects the modular nature of human disease genetics. Thus, phenotype mapping may be used to predict candidate genes for diseases as well as functional relations between genes and proteins. Such predictions will further improve if a unified system of phenotype descriptors is developed. The phenotype similarity data are accessible through a web interface at http://www.cmbi.ru.nl/MimMiner/