Low nasal carriage of drug-resistant bacteria among medical students in Vienna

Background: Multi-drug resistant bacteria are increasing and remain a major public health challenge worldwide. In order to understand the potential role of medical students as a reservoir for circulating pathogenic bacteria and their transmission, we analysed the nasal colonisation among 86 clinically exposed medical students of the Medical University of Vienna, which is integrated into General Hospital of Vienna

Efficacy of Fosfomycin in Experimental Osteomyelitis Due to Methicillin-Resistant Staphylococcus aureus▿

The activity of fosfomycin was evaluated in an experimental methicillin-resistant Staphylococcus aureus (MRSA) osteomyelitis model. Eighteen rats were treated for 4 weeks with 150 mg of fosfomycin/kg of body weight intraperitoneally once daily or with saline placebo. After treatment, animals were euthanized and the infected tibiae were processed for quantitative bacterial culture. Bone cultures were positive for methicillin-resistant S. aureus in all 9 (100%) untreated controls and in 2 of 9 (22.2%) fosfomycin-treated rats. Thus, fosfomycin treatment was significantly more efficacious than placebo. No development of resistance was observed after the 4-week treatment period

Daptomycin, Fosfomycin, or Both for Treatment of Methicillin-Resistant Staphylococcus aureus Osteomyelitis in an Experimental Rat Model▿

The in vivo activities of daptomycin, fosfomycin, and a combination of both antibiotics against a clinical isolate of methicillin-resistant Staphylococcus aureus (daptomycin MIC, 0.25 μg/ml; fosfomycin MIC, 0.5 μg/ml) were evaluated in a rat model of osteomyelitis. A total of 37 rats with experimental osteomyelitis were treated for 4 weeks with either 60 mg/kg of body weight of daptomycin subcutaneously once daily, 75 mg/kg fosfomycin intraperitoneally once daily, a combination of both drugs, or a saline placebo. After the completion of treatment, animals were euthanized, and the infected tibiae were processed for quantitative bacterial culture. Bone cultures were found to be positive for methicillin-resistant S. aureus in 9 of 9 (100%) animals of the placebo group, in 9 of 9 (100%) animals treated with daptomycin, in 1 of 10 (10%) fosfomycin-treated rats, and in 1 of 9 (22.2%) rats comprising the combination group. Results of bacterial counts in the bone samples were expressed as log10 CFU/g of bone and analyzed by using the Mann-Whitney U test followed by Bonferroni's multiple-comparison test. Based on bacterial counts, treatment with daptomycin was significantly superior to placebo, although it remained inferior to treatment with fosfomycin. No synergistic or antagonistic effect was observed for the combination therapy. No development of resistance against daptomycin or fosfomycin was observed after the 4-week treatment period

A Genetic rule-based expressive performance model for jazz saxophone

We describe an evolutionary approach to inducing a generative model of expressive music performance for Jazz saxophone. We begin with a collection of audio recordings of real Jazz saxophone performances from which we extract a symbolic representation of the musician's expressive performance. We then apply an evolutionary algorithm to the symbolic representation in order to obtain computational models for different aspects of expressive performance. Finally, we use these models to automatically synthesize performances with the timing and energy expressiveness that characterizes the music generated by a professional saxophonist.This work is supported by the Spanish TIN Project ProSeMus (TIN2006- 14932- C02- 01)

Relational IBL in music with a new structural similarity measure

Abstract. It is well known that many hard tasks considered in machine learning and data mining can be solved in an rather simple and robust way with an instance- and distance-based approach. In this paper we present another difficult task: learning, from large numbers of performances by concert pianists, to play music expressively. We model the problem as a multi-level decomposition and prediction task. Motivated by structural characteristics of such a task, we propose a new relational distance measure that is a rather straightforward combination of two existing measures. Empirical evaluation shows that our approach is in general viable and our algorithm, named DISTALL, is indeed able to produce musically interesting results. The experiments also provide evidence of the success of ILP in a complex domain such as music performance: it is shown that our instance-based learner operating on structured, relational data outperforms a propositional k-NN algorithm