Use of performic acid oxidation to expand the mass distribution of tryptic peptides

Significant identification of proteins by mass fingerprinting and partial sequencing of tryptic peptides is central to proteomics. However, peptide masses cluster with distances of approximately 1 Da. Expanding these clusters will give more peptides of unique masses, thereby identifying proteins with a higher significance. The mass clusters can be expanded downward by including more oxygen atoms in the peptides. Classic performic acid oxidation modifies three residues, Cys to CysO(3), Met to MetO(2), and Trp to TrpO(2). In this study, we compare the mass distributions of tryptic peptides computed from the predicted proteomes of Bacillus subtilis, Drosophila melanogaster, Arabidopsis thaliana, and Homo sapiens modified by oxidation, reduction, and reduction followed by carboxymethylation, carboxamidomethylation, or pyridylethylation. Forty to 46% of the eukaryotic tryptic peptides contain Cys, Met, or Trp. Additionally, the importance of mass accuracy of differentially modified tryptic peptides for significant protein identification by database searches was analyzed. The results show that performic acid oxidation gives markedly extended mass distributions at mass accuracies from +/-0.002 to +/-0.25 Da for the eukaryotes. The effect of the expanded mass distribution on significant protein identification was illustrated by searching simulated mass peak lists against the databases containing oxidized and reduced tryptic peptides. The specificity of formic acid oxidation was tested experimentally, and no general adverse effects were detected. Tryptic peptides provided a 100% sequence coverage of oxidized barley grain peroxidase by LC-MS, and the sequence coverages of oxidized and carboxymethylated bovine serum albumin were similar by MALDI-TOF MS analyses.     

The effect of ammonium ions on oxygen reduction and hydrogen peroxide formation on polycrystalline Pt electrodes

The influence of ammonium ions on the activity and selectivity of the electrocatalytic oxygen reduction reaction (ORR) on polycrystalline Pt was investigated in model studies under continuous mass transport, both in sulfuric and perchloric acid solutions. Ammonium was found to increase the yield of hydrogen peroxide, particularly in sulfuric acid, but also in perchloric acid solutions, and also at higher potentials (0.80–0.90 V_RHE) typical for fuel cell cathode operation, which may severely impair the long-term stability of membranes and electrodes in fuel cells exposed to fuel gases and/or air containing ammonia. Adsorbed species, assigned to ammonia and nitric oxide, were identified on a Pt film electrode using in situ FTIR spectroscopy. Adsorbed nitric oxide could only be observed in perchloric acid solutions. The higher coverage of adsorbed ammonia in sulfuric acid solution is attributed to a stabilization by coadsorbed (bi-)sulfate species; the higher total coverage in this electrolyte can explain the larger effect of ammonium ions on the ORR activity and selectivity in sulfuric compared to perchloric acid solution.     

Effects of initial molecular weight on removal rate of dextran in biofilms

Degradation kinetics of different size dextrans in a biofilm reactor were evaluated. Degradation rates of dextran standards, measured as time series of oxygen utilisation rates, decreased with increasing initial molecular weight. Removal of bulk phase total organic carbon with time was highly correlated (R2>0.99) and could be modelled with variable half-order degradation rate expressions. A power correlation between initial molecular weight and the variable half-order degradation rate coefficient was found for polymers in the range 6-500 kDa. Degradation of dextran in the colloid size range (MW>1 Mda) did not follow the same kinetics. Reductions in the observed removal rate with polymer size can be explained by the effect of reduced diffusivities of the substrate, without assuming reaction rate effects.     

Effects of bitterness, roughness, PROP taster status, and fungiform papillae density on bread acceptance

The purpose of this study was to determine how bitterness, roughness, color, perceived 6-n-propylthiouracil (PROP) intensity, and fungiform papillae density affect bread liking. To accomplish this, 78 subjects rated their liking for bread samples that were manipulated to vary independently in bitterness (provided by added wheat germ extract), roughness (provided by added bleached bran), and darkness (provided by added caramel color). The bitterness from added germ extract decreased bread liking. The roughness from the bleached bran increased bread liking; this increase was larger for subjects with higher fungiform papillae densities and was larger for subjects less sensitive to PROP.Added color decreased liking for subjects who preferred refined bread, but it increased liking for subjects who preferred whole wheat bread.     

Statistical and Thurstonian models for the A-not A protocol with and without sureness

The A-not A protocol with sureness produce multinomial observations that are traditionally analyzed with statistical methods for contingency tables or by calculation of an R-index. In this paper it is shown that the Thurstonian model for the A-not A protocol can be written as a cumulative link model including the binormal unequal variances model. The model is extended to allow for explanatory variables and we illustrate how consumer differences can be modeled within the Thurstonian framework on a consumer study of packet soup conducted by Unilever. The extension also allows several test-product variations to be analyzed in the same model providing additional insight and reduced experimental costs. The effects of explanatory variables on the Thurstonian delta, the sensitivity (AUC), the ROC curve and the response category thresholds are discussed in detail. All statistical methods are implemented in the free R-package ordinal (http://www.cran.r-project.org/package=ordinal/).     

Micromechanical Testing of Fracture Initiation Sites in Welded High-Strength Low-Alloy Steel

Micropillar compression tests were performed on martensite (M) and retained austenite (A) containing constituents formed in high-strength low-alloy steel after simulated thermal weld heat treatment. Due to the complicated fine microstructure of the constituent, the resulted stress–strain curves were further analyzed by considering the post-mortem scanning electron micrographs and the morphology of the deformation of the pillars. It was possible to obtain relevant data for the uniaxial stress–strain behavior of the M–A constituent in the studied steel. Microvickers measurements, which were converted to macroscopic yield stress by empirical relations, were compared with the micropillar compression test results. Comparison showed that these empirical relations are overestimating the obtained mechanical properties of the M–A constituents.     

Methodological guidelines for developing accident modification functions

This paper proposes methodological guidelines for developing accident modification functions. An accident modification function is a mathematical function describing systematic variation in the effects of road safety measures. The paper describes ten guidelines. An example is given of how to use the guidelines. The importance of exploratory analysis and an iterative approach in developing accident modification functions is stressed. The example shows that strict compliance with all the guidelines may be difficult, but represents a level of stringency that should be strived for. Currently the main limitations in developing accident modification functions are the small number of good evaluation studies and the often huge variation in estimates of effect. It is therefore still not possible to develop accident modification functions for very many road safety measures.     

Remote Patient Monitoring Within a Future 5G Infrastructure

Systems of wearable or implantable medical devices (IMD), sensor systems for monitoring and transmitting physiological recorded signals, will in future health care services be used for purposes of remote monitoring. Today, there exist several constraints, probably preventing the adoption of such services in clinical routine work. Within a future 5G infrastructure, new possibilities will be available due to improved addressing solutions and extended security services in addition to higher bandwidth in the wireless communication link. Thus 5G solutions can represent a paradigm shift regarding remote patient’s monitoring and tracking possibilities, with enhancement in transmitting information between patients and health care services. Some aspects of new possibilities are highlighted in describing a realistic scenario within a future 5G framework.     

Publication bias and time-trend bias in meta-analysis of bicycle helmet efficacy: a re-analysis of Attewell, Glase and McFadden, 2001

This paper shows that the meta-analysis of bicycle helmet efficacy reported by Attewell, Glase, and McFadden (Accident Analysis and Prevention 2001, 345–352) was influenced by publication bias and time-trend bias that was not controlled for. As a result, the analysis reported inflated estimates of the effects of bicycle helmets. This paper presents a re-analysis of the study. The re-analysis included: (1) detecting and adjusting for publication bias by means of the trim-and-fill method; (2) ensuring the inclusion of all published studies by means of continuity corrections of estimates of effect rely on zero counts; (3) detecting and trying to account for a time-trend bias in estimates of the effects of bicycle helmets; (4) updating the study by including recently published studies evaluating the effects of bicycle helmets. The re-analysis shows smaller safety benefits associated with the use of bicycle helmets than the original study.     

Effect of thermostat and window opening occupant behavior models on energy use in homes

Existing dynamic energy simulation tools exceed the static dimension of the simplified methods through a better and more accurate prediction of energy use; however, their ability to predict real energy consumption is undermined by a weak representation of human interactions with the control of the indoor environment. The traditional approach to building dynamic simulation considers energy consumption as fully deterministic, taking into account standardized input parameters and using fixed and unrealistic schedules (lighting level, occupancy, ventilation rate, thermostat set-point). In contrast, in everyday practice occupants interact with the building plant system and building envelope in order to achieve desired indoor environmental conditions. In this study, occupant behavior in residential building was modelled accordingly to a probabilistic approach. A new methodology was developed to combine probabilistic user profiles for both window opening and thermostat set-point adjustments into one building energy model implemented in the dynamic simulation tool IDA Ice. The aim of the study was to compare mean values of the probabilistic distribution of the obtained results with a singular heating energy consumption value obtained by means of standard deterministic simulations. Major findings of this research demonstrated the weakness of standardized occupant behavior profile in energy simulation tools and the strengths of energy models based on measurements in fields and probabilistic modelling providing scenarios of occupant behavior in buildings.