Proteome Analysis of Subsarcolemmal Cardiomyocyte Mitochondria: A Comparison of Different Analytical Platforms

Mitochondria are complex organelles that play critical roles in diverse aspects of cellular function. Heart disease and a number of other pathologies are associated with perturbations in the molecular machinery of the mitochondria. Therefore, comprehensive, unbiased examination of the mitochondrial proteome represents a powerful approach toward system-level insights into disease mechanisms. A crucial aspect in proteomics studies is design of bioanalytical strategies that maximize coverage of the complex repertoire of mitochondrial proteins. In this study, we evaluated the performance of gel-based and gel-free multidimensional platforms for profiling of the proteome in subsarcolemmal mitochondria harvested from rat heart. We compared three different multidimensional proteome fractionation platforms: polymeric reversed-phase liquid chromatography at high pH (PLRP), sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), and isoelectric focusing (IEF) separations combined with liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS), and bioinformatics for protein identification. Across all three platforms, a total of 1043 proteins were identified. Among the three bioanalytical strategies, SDS-PAGE followed by LC-MS/MS provided the best coverage of the mitochondrial proteome. With this platform, 890 proteins with diverse physicochemical characteristics were identified; the mitochondrial protein panel encompassed proteins with various functional roles including bioenergetics, protein import, and mitochondrial fusion. Taken together, results of this study provide a large-scale view of the proteome in subsarcolemmal mitochondria from the rat heart, and aid in the selection of optimal bioanalytical platforms for differential protein expression profiling of mitochondria in health and disease.     

A smartphone-based fall detection system

Falls are a major cause of injuries and hospital admissions among elderly people. Thus, the caregiving process and the quality of life of older adults can be improved by adopting systems for the automatic detection of falls. This paper presents a smartphone-based fall detection system that monitors the movements of patients, recognizes a fall, and automatically sends a request for help to the caregivers. To reduce the problem of false alarms, the system includes novel techniques for the recognition of those activities of daily living that could be erroneously mis-detected as falls (such as sitting on a sofa or lying on a bed). To limit the intrusiveness of the system, a small external sensing unit can also be used for the acquisition of movement data.     

Estimation of the mass of powder trapped at collision during ball milling from the kinetics of the mechanically activated decomposition of Ag oxalate

The present work aims at providing a direct experimental estimate of the amount of powder trapped at each collision during the mechanical processing by ball milling. Attention has been focused on the mechanochemical reactivity of anhydrous Ag oxalate powders, prepared by mixing Ag nitrate and Na oxalate aqueous solutions, and then filtering and drying the white precipitate formed. Suitable amounts of such powders were mechanically processed with a single milling ball. The mechanical processing induced the gradual decomposition of Ag oxalate into Ag and carbon dioxide. The process was followed by gravimetric analyses, and its kinetics related to individual collisions. It is shown that the decomposition process follows a simple exponential kinetics, which allows the identification and evaluation of an apparent rate constant. This can be regarded as a measure of the amount of powder trapped at each collision, which is roughly equal to 0.41 mg.     

Absence of allergenic residues in experimental and commercial wines fined with caseinates

The possible presence of allergenic residues in wines treated with one of the potassium caseinates used as fining agents has been investigated.     

Thermoacoustic Emission from Carbon Nanotubes Imaged by Atomic Force Microscopy

The thermoacoustic effect of isolated single‐wall carbon nanotubes aligned between electrodes is experimentally observed for the first time by imaging the emitted acoustic wave using an atomic force microscopy‐based technique specifically developed for the task. The capability of such a technique for single‐point thermoacoustic measurements is first verified on carbon nanotubes layers with two electrodes for injecting alternate electric current. The technique is then demonstrated to allow the acquisition, simultaneously with the topography, of images reflecting the pressure of the acoustic wave at fixed distance from the sample. Such a capability is used to collect images reflecting the amplitude of acoustic waves generated by isolated nanotubes and nanotube bundles by the thermoacoustic effect.     

Novel quasi-autothermal hydrogen production process in a fixed-bed using a chemical looping approach: A numerical study

This paper presents a novel quasi-autothermal hydrogen production process. The proposed layout couples a Chemical Looping Combustion (CLC) section and a Steam Methane Reforming (SMR) one. In CLC section, four packed-beds are operated using Ni as oxygen carrier and CH₄ as fuel to continuously produce a hot gaseous mixture of H₂O and CO₂. In SMR section, two fixed-beds filled with Ni-based catalyst convert CH₄ and H₂O into a H₂-rich syngas. Four heat exchangers were employed to recover residual heat content of all the exhaust gas currents. By means of a previously developed 1D numerical model, a dynamic simulation study was carried out to evaluate feasibility of the proposed system in terms of methane conversion (100% circa), hydrogen yield (about 0.65 mol_H2/mol_CH4) and selectivity (about 70%), and syngas ratio (about 2.3 mol_H2/mol_CO). Energetic and environmental analyses of the system performed with respect to conventional steam methane reforming, highlights an energy saving of about 98% and avoided CO₂ emission of about 99%.     

Performance optimization of polymer electrolyte membrane fuel cells using the Nelder-Mead algorithm

The direct-search simplex method for function optimization has been adapted to performance optimization of polymer electrolyte membrane fuel cells (PEMFCs). The established method is strongly application oriented and uses only experimentally determined data for optimization. It is not restricted to discrete parameters optimums and does not require the use of third-party software or computational resources. Hence, it is easy to implement in fuel cell testing stations. The optimization consists of finding, for a given fuel cell load, an optimum set of values of the 7 fuel cell operating parameters: the fuel cell temperature, the reactants' stoichiometric ratios, the reactants' inlet relative humidity, and the reactants' outlet pressures, resulting in the highest fuel cell performance. The performance is measured using a scalar function of the operating parameters and the load and can be defined according to needs.Two PEMFC performance functions: the fuel cell voltage and the system-related fuel cell efficiency were optimized using the procedure for practically sized PEMFC stacks of two designs. With respect to the nominal operating conditions defined as optimal for each stack design by its manufacturer, the gains from the optimization procedure were up to over 12% and up to over 7% for the stack voltage and efficiency, respectively. The validation of the procedure involved 5 stack specimens and four laboratories and consistent results were obtained.