Molecular identification and cluster analysis of homofermentative thermophilic lactobacilli isolated from dairy products

Twenty-five strains of thermophilic lactobacilli isolated from yoghurt and from semi-hard and hard cheeses (in parallel with nine type or reference strains) were identified and grouped according to their genetic relatedness. Strains were identified by sugar fermentation patterns using the "API 50 CHL" galleries, by species-specific DNA probes in dot-blot hybridization experiments, by amplification and restriction analysis of the 16S rRNA gene (ARDRA) and by polymerase chain reaction (PCR) using species-specific oligonucleotide primers. Strains were classified as Lactobacillus delbrueckii subsp. lactis and subsp. bulgaricus, L. helveticus, and L. acidophilus. Strains which were atypical by sugar fermentation patterns were also identified. Most of the strains could not be grouped using carbohydrate fermentation profiles. PCR fingerprinting was used to identify DNA profiles for the 25 lactobacilli. Experimentally obtained PCR profiles enabled discrimination of all strains, which were grouped according to the similarities in their combined patterns. In general, the clustering of the strains corresponded well with species delineation obtained by molecular identification. The dendrogram of genetic relatedness enabled the unambiguous identification of most of the strains which were shown to be atypical by the sugar fermentation profile, except for a discrepancy in one L. delbrueckii subsp. lactis strain and one atypical Lactobacillus sp. strain.     

Molecular analysis of the functional role of beta-adrenergic receptor kinase 1 amino-terminal

Receptor phosphorylation is a key step in the process of rapid desensitization. beta-adrenergic receptor kinase (betaARK) is a specific receptor kinase that is known to phosphorylate and induce desensitization of several G-coupled receptors only when they are occupied by their agonists. In the present study we have done several modifications to the amino-terminal of betaARK1, in order to clarify its functional role. The recombinant mutants were tested for their ability to phosphorylate rhodopsin present in purified bovine ROS membranes which serves as a substrate for betaARK1. Their expression levels were detected by Western blot analysis. We found that when the amino-terminal of betaARK1 is modified its expression level is very low, hence it is not able to phosphorylate over the basal. These findings suggest that this region is crucial for the normal processing of the protein.     

Enhancement of Peroxidase Activity in Artificial Mimochrome VI Catalysts through Rational Design

Rational design provides an attractive strategy to tune and control the reactivity of bioinspired catalysts. Although there has been considerable progress in the design of heme oxidase mimetics with active‐site environments of ever‐growing complexity and catalytic efficiency, their stability during turnover is still an open challenge. Herein, we show that the simple incorporation of two 2‐aminoisobutyric acids into an artificial peptide‐based peroxidase results in a new catalyst (Fe^III‐MC6*a) with higher resistance against oxidative damage and higher catalytic efficiency. The turnover number of this catalyst is twice as high as that of its predecessor. These results point out the protective role exerted by the peptide matrix and pave the way to the synthesis of robust bioinspired catalysts.     

Evaluation of a comprehensive slip, trip and fall prevention programme for hospital employees

In 2007, the Bureau of Labor Statistics reported that the incidence rate of lost workday injuries from slips, trips and falls (STFs) on the same level in hospitals was 35.2 per 10,000 full-time equivalents (FTE), which was 75% greater than the average rate for all other private industries combined (20.2 per 10,000 FTEs). The objectives of this 10-year (1996-2005) longitudinal study were to: 1) describe occupational STF injury events in hospitals; 2) evaluate the effectiveness of a comprehensive programme for reducing STF incidents among hospital employees. The comprehensive prevention programme included analysis of injury records to identify common causes of STFs, on-site hazard assessments, changes to housekeeping procedures and products, introduction of STF preventive products and procedures, general awareness campaigns, programmes for external ice and snow removal, flooring changes and slip-resistant footwear for certain employee subgroups. The hospitals' total STF workers' compensation claims rate declined by 58% from the pre-intervention (1996-1999) rate of 1.66 claims per 100 FTE to the post-intervention (2003-2005) time period rate of 0.76 claims per 100 FTE (adjusted rate ratio = 0.42, 95% CI: 0.33-0.54). STFs due to liquid contamination (water, fluid, slippery, greasy and slick spots) were the most common cause (24%) of STF claims for the entire study period 1996-2005. Food services, transport/emergency medical service and housekeeping staff were at highest risk of a STF claim in the hospital environment. Nursing and office administrative staff generated the largest numbers of STF claims. STF injury events in hospitals have a myriad of causes and the work conditions in hospitals are diverse. This research provides evidence that implementation of a broad-scale prevention programme can significantly reduce STF injury claims.     

DANCo: An intrinsic dimensionality estimator exploiting angle and norm concentration

In the past decade the development of automatic intrinsic dimensionality estimators has gained considerable attention due to its relevance in several application fields. However, most of the proposed solutions prove to be not robust on noisy datasets, and provide unreliable results when the intrinsic dimensionality of the input dataset is high and the manifold where the points are assumed to lie is nonlinearly embedded in a higher dimensional space. In this paper we propose a novel intrinsic dimensionality estimator (DANCo) and its faster variant (FastDANCo), which exploit the information conveyed both by the normalized nearest neighbor distances and by the angles computed on couples of neighboring points. The effectiveness and robustness of the proposed algorithms are assessed by experiments on synthetic and real datasets, by the comparative evaluation with state-of-the-art methodologies, and by significance tests.     

Strategic decision making on complex systems

In this paper, we propose a challenging research direction for Constraint Programming and optimization techniques in general. We address problems where decisions to be taken affect and are affected by complex systems, which exhibit phenomena emerging from a collection of interacting objects, capable to self organize and to adapt their behaviour according to their history and feedback. Such systems are unfortunately impervious to modeling efforts via state-of-the-art combinatorial optimization techniques. We provide some hints on approaches to connect and integrate decision making and optimization technology with complex systems via machine learning, game theory and mechanism design. In the first case, the aim is to extract modeling components to express the relation between global decisions and observables emerging from the real system, or from an accurate predictive model (e.g. a simulator). In the second case, the idea is to exploit game theory, mechanism design and distributed decision making to drive the process toward realistic equilibrium points avoiding globally optimal, but unrealistic, configurations. We conclude by observing how dealing with the complexity of the considered problems will require to greatly extend the capabilities of state of the art solvers: in this context, we identify some key issues and highlight future research directions.     

De novo design of helical bundles as models for understanding protein folding and function

De novo protein design has proven to be a powerful tool for understanding protein folding, structure, and function. In this Account, we highlight aspects of our research on the design of dimeric, four-helix bundles. Dimeric, four-helix bundles are found throughout nature, and the history of their design in our laboratory illustrates our hierarchic approach to protein design. This approach has been successfully applied to create a completely native-like protein. Structural and mutational analysis allowed us to explore the determinants of native protein structure. These determinants were then applied to the design of a dinuclear metal-binding protein that can now serve as a model for this important class of proteins.