EPR Characterisation of the Ferrous Nitrosyl Complex Formed within the Oxygenase Domain of NO Synthase

Nitric oxide is produced in mammals by a class of enzymes called NO synthases (NOSs). It plays a central role in cellular signalling but also has deleterious effects, as it leads to the production of reactive oxygen and nitrogen species. NO forms a relatively stable adduct with ferrous haem proteins, which, in the case of NOS, is also a key catalytic intermediate. Despite extensive studies on the ferrous nitrosyl complex of other haem proteins (in particular myoglobin), little characterisation has been performed in the case of NOS. We report here a temperature‐dependent EPR study of the ferrous nitrosyl complex of the inducible mammalian NOS and the bacterial NOS‐like protein from Bacillus subtilis. The results show that the overall behaviours are similar to those observed for other haem proteins, but with distinct ratios between axial and rhombic forms in the case of the two NOS proteins. The distal environment appears to control the existence of the axial form and the evolution of the rhombic form.     

Identifying Lysophosphatidic Acid Acyltransferase β (LPAAT-β) as the Target of a Nanomolar Angiogenesis Inhibitor from a Phenotypic Screen Using the Polypharmacology Browser PPB2

By screening a focused library of kinase inhibitor analogues in a phenotypic co-culture assay for angiogenesis inhibition, we identified an aminotriazine that acts as a cytostatic nanomolar inhibitor. However, this aminotriazine was found to be completely inactive in a whole-kinome profiling assay. To decipher its mechanism of action, we used the online target prediction tool PPB2 ( http://ppb2.gdb.tools ), which suggested lysophosphatidic acid acyltransferase β (LPAAT-β) as a possible target for this aminotriazine as well as several analogues identified by structure–activity relationship profiling. LPAAT-β inhibition (IC₅₀ ≈15 nm ) was confirmed in a biochemical assay and by its effects on cell proliferation in comparison with a known LPAAT-β inhibitor. These experiments illustrate the value of target-prediction tools to guide target identification for phenotypic screening hits and significantly expand the rather limited pharmacology of LPAAT-β inhibitors.     

Influence of the morphology on the fire behavior of a polycarbonate/poly(butylene terephthalate) blend

Polycarbonate/Poly(butylene terephthalate) (PC/PBT) blends are used in various industrial sectors, particularly in the cable industry. In this work, the fire behavior of PC/PBT blends was studied for the entire range of blend composition to investigate the relation between fire properties and blend morphology. The morphology of the binary blends used presents a phase inversion point for 25–30 wt % PBT. Various tests have been performed to characterize the fire behavior [limiting oxygen index (LOI), epiradiator test, cone calorimeter, and pyrolysis combustion flow calorimeter (PCFC)]. A change in fire behavior has been observed when the PBT content increases from 20 to 30 wt %, corresponding to the phase inversion, from a continuous rich-PC phase to a continuous rich-PBT phase. Consequently, it can be suggested that the control of the morphology of binary polymer blends is crucial to improve their fire properties. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Peptide Vectors Carry Pyrene to Cell Organelles Allowing Real-Time Quantification of Free Radicals in Mitochondria by Time-Resolved Fluorescence Microscopy

Real-time quantification of reactive nitrogen and oxygen species (ROS) in cells is of paramount importance as they are essential for cellular functions. Their excessive formation contributes to the dysfunction of cells and organisms, ultimately leading to cell death. As ROS are mostly produced in the mitochondria, we have synthesized a fluorescent probe able to reach this organelle to detect and quantify, in real time, the variation of ROS by time-resolved microfluorimetry. The new probes are based on the long fluorescence lifetime of pyrene butyric acid (PBA). Two PBA isomers, attached at their 1- or 2-positions to a peptide vector to target mitochondria, were compared and were shown to allow the measurement of free radical species and oxygen, but not non-radical species such as H₂O₂.     

Spark plasma sintering of a p-type Si1?x Ge x alloy: identification of the densification mechanism by isothermal and anisothermal methods

Spark plasma sintering of a p-type Si_0.795Ge_0.200B_0.005 alloy has been investigated in vacuum, in the 400–1200 °C temperature range. The densification mechanism has been determined using isothermal and anisothermal methods. In spite of a slight material degradation for the highest sintering temperatures (occurrence of cristobalite nodules homogeneously dispersed in intergranular and intragranular positions), it is proposed that densification proceeds by grain boundary sliding accommodated most probably by silicon volume diffusion. The microstructure observation of several sintered samples using transmission electron microscopy supports the densification mechanism advanced. Because the elemental grains remain mostly equiaxe whatever the sintering conditions, a grain intercalation mechanism may be also implicated during densification.     

Predicting Enhanced Vegetation Index (EVI) curves for ecosystem modeling applications

Vegetation indices derived from remote sensing data provide information about the variability in stature, growth and vigor of the vegetation across a region, and have been used to model plant processes. For example, the Enhanced Vegetation Index (EVI) provides a measure of greenness of the vegetation that can be used to predict net primary production. However, ecosystem models relying on remote sensing data for EVI or other vegetation indices are limited by the time series of the satellite data record. Our objective was to develop a statistical model to predict EVI in order to extend the time series for modeling applications. To explain the functional behavior of the seasonal EVI curves, a two-stage multiple regression fitting procedure within a semi-parametric mixed effect (SPME) model framework was used. First, a linear mixed effect (LME) model was fitted to the EVI with climate indexes, crop and irrigation information as predictor variables. Second, Penalized B-splines were used to explain the behavior of the smooth residuals, which result from a smooth model fit to the smooth EVI data curve, in order to describe the uncertainty of the EVI curve. Individual models were fit within individual Major Land Resources Areas (MLRAs). Predicted seasonal EVI, derived from our regression equations, showed a strong agreement with the observed EVI and was able to capture the site by site and year by year variation in the EVI curve. Out-of-sample prediction produced excellent results for a majority of the sites, except for sites without clear seasonal patterns, which may have resulted from cloud contamination and/or snow cover. Therefore, given the appropriate climate, crop, and irrigation information, the proposed approach can be used to predict seasonal EVI curves for extending the time series into the past and future.