Cardiovascular effects of variations in habitual levels of physical activity

Mechanisms involved in human cardiovascular adaption to stress, particularly adaption to different levels of physical activity are determined along with quantitative noninvasive methods for evaluation of cardiovascular function during stess in normal subjects and in individuals with latent or manifest cardiovascular disease. Results are summarized

The developmental cell biology of Trypanosoma brucei

Trypanosoma brucei provides an excellent system for studies of many aspects of cell biology, including cell structure and morphology, organelle positioning, cell division and protein trafficking. However, the trypanosome has a complex life cycle in which it must adapt either to the mammalian bloodstream or to different compartments within the tsetse fly. These differentiation events require stage-specific changes to basic cell biological processes and reflect responses to environmental stimuli and programmed differentiation events that must occur within a single cell. The organization of cell structure is fundamental to the trypanosome throughout its life cycle. Modulations of the overall cell morphology and positioning of the specialized mitochondrial genome, flagellum and associated basal body provide the classical descriptions of the different life cycle stages of the parasite. The dependency relationships that govern these morphological changes are now beginning to be understood and their molecular basis identified. The overall picture emerging is of a highly organized cell in which the rules established for cell division and morphogenesis in organisms such as yeast and mammalian cells do not necessarily apply. Therefore, understanding the developmental cell biology of the African trypanosome is providing insight into both fundamentally conserved and fundamentally different aspects of the organization of the eukaryotic cell

Charging and coagulation of dust in protoplanetary plasma environments

Combining a particle-particle, particle-cluster and cluster-cluster agglomeration model with an aggregate charging model, the coagulation and charging of dust particles in various plasma environments relevant for proto-planetary disks have been investigated. The results show that charged aggregates tend to grow by adding small particles and clusters to larger particles and clusters, leading to greater sizes and masses as compared to neutral aggregates, for the same number of monomers in the aggregate. In addition, aggregates coagulating in a Lorentzian plasma (containing a larger fraction of high-energy plasma particles) are more massive and larger than aggregates coagulating in a Maxwellian plasma, for the same plasma densities and characteristic temperature. Comparisons of the grain structure, utilizing the compactness factor, {\phi}{\sigma}, demonstrate that a Lorentzian plasma environment results in fluffier aggregates, with small {\phi}{\sigma}, which exhibit a narrow compactness factor distribution. Neutral aggregates are more compact, with larger {\phi}{\sigma}, and exhibit a larger variation in fluffiness. Measurement of the compactness factor of large populations of aggregates is shown to provide information on the disk parameters that were present during aggregation

Antimicrobial and antibiofilm activity and machine learning classification analysis of essential oils from different mediterranean plants against pseudomonas aeruginosa

Pseudomonas aeruginosa is a ubiquitous organism and opportunistic pathogen that can cause persistent infections due to its peculiar antibiotic resistance mechanisms and to its ability to adhere and form biofilm. The interest in the development of new approaches for the prevention and treatment of biofilm formation has recently increased. The aim of this study was to seek new non-biocidal agents able to inhibit biofilm formation, in order to counteract virulence rather than bacterial growth and avoid the selection of escape mutants. Herein, different essential oils extracted from Mediterranean plants were analyzed for their activity againstP. aeruginosa. Results show that they were able to destabilize biofilm at very low concentration without impairing bacterial viability. Since the action is not related to a bacteriostatic/bactericidal activity onP. aeruginosa, the biofilm change of growth in presence of the essential oils was possibly due to a modulation of the phenotype. To this aim, application of machine learning algorithms led to the development of quantitative activity-composition relationships classification models that allowed to direct point out those essential oil chemical components more involved in the inhibition of biofilm production. The action of selected essential oils on sessile phenotype make them particularly interesting for possible applications such as prevention of bacterial contamination in the community and in healthcare environments in order to prevent human infections. We assayed 89 samples of different essential oils asP. aeruginosaanti-biofilm. Many samples inhibitedP. aeruginosabiofilm at concentrations as low as 48.8 µg/mL. Classification of the models was developed through machine learning algorithms