Effectiveness of Two Different Fluoride-Based Agents in the Treatment of Dentin Hypersensitivity: A Prospective Clinical Trial

Hyperesthesia is related to increased sensitivity of dental tissues to mechanical, chemical and thermal stimuli. The aim of this prospective clinical trial was to compare the effectiveness of a calcium-fluoride-forming agent (Tiefenfluorid®, Humanchemie GmbH, Alfeld, Germany) with that of a fluoride varnish (Enamelast™, Ultradent Inc., Cologne, Germany) in the treatment of dental hyperesthesia in adult patients. In total, 176 individuals (106 females and 70 males, aged 18–59 years old) diagnosed with dental hyperesthesia (DH) were enrolled. The main clinical symptoms were hyperesthesia from coldness and sweetness during chewing; the types of clinical lesions were also determined and recorded. The patients were selected randomly and divided into two groups: (i) the first group of 96 patients was treated with Tiefenfluorid® applied in three appointments at 7-day intervals; (ii) the second group of 80 patients was treated with Enamelast™, applied seven times at 7-day intervals. All the patients were recalled 7 days, 14 days, 1 month, 3 months, and 6 months from the last application. At the baseline and during every follow-up visit, the DH was measured with a pulp tester. A random intercept/random slope model was used to evaluate the effect of the treatment, at various times with respect to the initial diagnosis. Within the limits of the present study, Tiefenfluorid® was more effective than Enamelast™ against DH in that it provided long-lasting results, with a significant improvement still detected at the latest 6-month follow-up

A Mighty Small Heart: The Cardiac Proteome of Adult Drosophila melanogaster

Drosophila melanogaster is emerging as a powerful model system for the study of cardiac disease. Establishing peptide and protein maps of the Drosophila heart is central to implementation of protein network studies that will allow us to assess the hallmarks of Drosophila heart pathogenesis and gauge the degree of conservation with human disease mechanisms on a systems level. Using a gel-LC-MS/MS approach, we identified 1228 protein clusters from 145 dissected adult fly hearts. Contractile, cytostructural and mitochondrial proteins were most abundant consistent with electron micrographs of the Drosophila cardiac tube. Functional/Ontological enrichment analysis further showed that proteins involved in glycolysis, Ca2+-binding, redox, and G-protein signaling, among other processes, are also over-represented. Comparison with a mouse heart proteome revealed conservation at the level of molecular function, biological processes and cellular components. The subsisting peptidome encompassed 5169 distinct heart-associated peptides, of which 1293 (25%) had not been identified in a recent Drosophila peptide compendium. PeptideClassifier analysis was further used to map peptides to specific gene-models. 1872 peptides provide valuable information about protein isoform groups whereas a further 3112 uniquely identify specific protein isoforms and may be used as a heart-associated peptide resource for quantitative proteomic approaches based on multiple-reaction monitoring. In summary, identification of excitation-contraction protein landmarks, orthologues of proteins associated with cardiovascular defects, and conservation of protein ontologies, provides testimony to the heart-like character of the Drosophila cardiac tube and to the utility of proteomics as a complement to the power of genetics in this growing model of human heart disease

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

This work was in part supported by the PRIME-XS project, grant agreement number 262067, funded by the European Union seventh Framework Programme; The Netherlands Proteomics Centre, embedded in The Netherlands Genomics Initiative; The Netherlands Bioinformatics Centre; and the Centre for Biomedical Genetics (to S.C., B.B. and A.J.R.H); by NIH grants NCRR RR001614 and RR019934 (to the UCSF Mass Spectrometry Facility, director: A.L. Burlingame, P.B.); and by grants from the MRC, CR-UK, BBSRC and Barts and the London Charity (to P.C.

Generating and navigating proteome maps using mass spectrometry

Proteomes, the ensembles of all proteins expressed by cells or tissues, are typically analysed by mass spectrometry. Recent technical and computational advances have greatly increased the fraction of a proteome that can be identified and quantified in a single study. Current mass spectrometry-based proteomic strategies have the potential to reproducibly, accurately, quantitatively and comprehensively measure any protein or whole proteomes from cells and tissues at different states. Achieving these goals will require complete proteome maps and analytical strategies that use these maps as prior information and will greatly enhance the impact of proteomics on biological and clinical research

From enzyme kinetics to metabolic network modeling - visualization tool for enhanced kinetic analysis of biochemical network models

Model-based analysis of enzyme kinetics allows the determination of optimal conditions for their use in biocatalysis. For biotransformations or fermentative approaches the modeling of metabolic pathways or complex metabolic networks is necessary to obtain model-based predictions of steps which limit product formation within the network. To set up adequate kinetic models, relevant mechanistic information about enzyme properties is required and can be taken from in vitro studies with isolated enzymes or from in vivo investigations using stimulus-response experiments which provide a lot of kinetic information about the metabolic network. But with increasing number of reaction steps and regulatory interdependencies in the network structure the amount of simulation data dramatically increases and the simulation results from the dynamic models become difficult to analyze and interpret. Demonstrated for an Escherichia coli model of the central carbon metabolism, methods for visualization and animation of simulation data were applied and extended to facilitate model analysis and biological interpretation. The dynamic metabolite pool and metabolic flux changes were visualized simultaneously by a software tool. In addition, a new quantification method for enzyme activation/inhibition was proposed, and this information was implemented in the metabolic visualization

Visualizing regulatory interdependencies and parameter sensitivities in biochemical network models

For the evaluation of data from stimulus response experiments dynamic metabolic network models are generated. With an increase of reaction steps and regulatory interdependencies the amount of the simulation data becomes hard to handle. In this paper, we present the application and extension of methods combining visualization and animation of dynamic models to facilitate the analysis of the complex system behaviour.The dynamic changes of metabolite pools and fluxes are simultaneous visualized within the network structure. Depending on the scaling used, different focuses can be set, e.g. to observe local dynamics or global concentration balances. For the visualization of the present inhibition and activation state of certain reaction steps of a metabolic network model a novel quantification method is proposed.The sensitivity analysis of dynamic metabolic network models leads to high-dimensional sensitivity matrices that vary over time. To process the enormous amount of data we use a colour scale transformation and the reorderable matrix method for the visual exploration of the time-varying matrices.The benefits of our methods are illustrated with the help of a metabolic network model of the central carbon metabolism in Escherichia coli. (C) 2008 IMACS. Published by Elsevier B.V. All rights reserved