Prospective ECG triggering reduces prosthetic heart valve-induced artefacts compared with retrospective ECG gating on 256-slice CT

Item does not contain fulltextOBJECTIVES: Multidetector computed tomography (MDCT) has diagnostic value for the evaluation of prosthetic heart valve (PHV) dysfunction but it is hampered by artefacts. We hypothesised that image acquisition using prospective triggering instead of retrospective gating would reduce artefacts related to pulsating PHV. METHODS: In a pulsatile in vitro model, a mono- and bileaflet PHV were imaged using 256 MDCT at 60, 75 and 90 beats per minute (BPM) with either retrospective gating (120 kV, 600 mAs, pitch 0.2, CTDI(vol) 39.8 mGy) or prospective triggering (120 kV, 200 mAs, CTDI(vol) 13.3 mGy). Two thresholds (>175 and <-45HU), derived from the density of surrounding structures, were used for quantification of hyper- and hypodense artefacts. Image noise and artefacts were compared between protocols. RESULTS: Prospective triggering reduced hyperdense artefacts for both valves at every BPM (P = 0.001 all comparisons). Hypodense artefacts were reduced for the monoleaflet valve at 60 (P = 0.009), 75 (P = 0.016) and 90 BPM (P = 0.001), and for the bileaflet valves at 60 (P = 0.001), 90 (P = 0.001) but not at 75 BPM (P = 0.6). Prospective triggering reduced image noise at 60 (P = 0.001) and 75 (P < 0.03) but not at 90 BPM. CONCLUSIONS: Compared with retrospective gating, prospective triggering reduced most artefacts related to pulsating PHV in vitro. KEY POINTS: * Computed tomographic images are often degraded by prosthetic heart valve-induced artefacts * Prospective triggering reduces prosthetic heart valve-induced artefacts in vitro * Artefact reduction at 90 beats per minute occurs without image noise reduction * Prospective triggering may improve CT image quality of moving hyperdense structures.1 juni 201

Accelerated apoptotic death and <i>in vivo</i> turnover of erythrocytes in mice lacking functional mitogen- and stress-activated kinase MSK1/2

The mitogen- and stress-activated kinase MSK1/2 plays a decisive role in apoptosis. In analogy to apoptosis of nucleated cells, suicidal erythrocyte death called eryptosis is characterized by cell shrinkage and cell membrane scrambling leading to phosphatidylserine (PS) externalization. Here, we explored whether MSK1/2 participates in the regulation of eryptosis. To this end, erythrocytes were isolated from mice lacking functional MSK1/2 (msk−/−) and corresponding wild-type mice (msk+/+). Blood count, hematocrit, hemoglobin concentration and mean erythrocyte volume were similar in both msk−/− and msk+/+ mice, but reticulocyte count was significantly increased in msk−/− mice. Cell membrane PS exposure was similar in untreated msk−/− and msk+/+ erythrocytes, but was enhanced by pathophysiological cell stressors ex vivo such as hyperosmotic shock or energy depletion to significantly higher levels in msk−/− erythrocytes than in msk+/+ erythrocytes. Cell shrinkage following hyperosmotic shock and energy depletion, as well as hemolysis following decrease of extracellular osmolarity was more pronounced in msk−/− erythrocytes. The in vivo clearance of autologously-infused CFSE-labeled erythrocytes from circulating blood was faster in msk−/− mice. The spleens from msk−/− mice contained a significantly greater number of PS-exposing erythrocytes than spleens from msk+/+ mice. The present observations point to accelerated eryptosis and subsequent clearance of erythrocytes leading to enhanced erythrocyte turnover in MSK1/2-deficient mice

Solvent accessible surface area approximations for rapid and accurate protein structure prediction

The burial of hydrophobic amino acids in the protein core is a driving force in protein folding. The extent to which an amino acid interacts with the solvent and the protein core is naturally proportional to the surface area exposed to these environments. However, an accurate calculation of the solvent-accessible surface area (SASA), a geometric measure of this exposure, is numerically demanding as it is not pair-wise decomposable. Furthermore, it depends on a full-atom representation of the molecule. This manuscript introduces a series of four SASA approximations of increasing computational complexity and accuracy as well as knowledge-based environment free energy potentials based on these SASA approximations. Their ability to distinguish correctly from incorrectly folded protein models is assessed to balance speed and accuracy for protein structure prediction. We find the newly developed “Neighbor Vector” algorithm provides the most optimal balance of accurate yet rapid exposure measures

Pb(II) Induces Scramblase Activation and Ceramide-Domain Generation in Red Blood Cells

The mechanisms of Pb(II) toxicity have been studied in human red blood cells using confocal microscopy, immunolabeling, fluorescence-activated cell sorting and atomic force microscopy. The process follows a sequence of events, starting with calcium entry, followed by potassium release, morphological change, generation of ceramide, lipid flip-flop and finally cell lysis. Clotrimazole blocks potassium channels and the whole process is inhibited. Immunolabeling reveals the generation of ceramide-enriched domains linked to a cell morphological change, while the use of a neutral sphingomyelinase inhibitor greatly delays the process after the morphological change, and lipid flip-flop is significantly reduced. These facts point to three major checkpoints in the process: first the upstream exchange of calcium and potassium, then ceramide domain formation, and finally the downstream scramblase activation necessary for cell lysis. In addition, partial non-cytotoxic cholesterol depletion of red blood cells accelerates the process as the morphological change occurs faster. Cholesterol could have a role in modulating the properties of the ceramide-enriched domains. This work is relevant in the context of cell death, heavy metal toxicity and sphingolipid signaling.AGA was a predoctoral student supported by the Basque Government and later by the University of the Basque Country (UPV/EHU). This work was also supported in part by grants from the Spanish Government (FEDER/MINECO BFU 2015-66306-P to F.M.G. and A.A.) and the Basque Government (IT849-13 to F.M.G. and IT838-13 to A.A.), and by the Swiss National Science Foundation

Rationalization and Design of the Complementarity Determining Region Sequences in an Antibody-Antigen Recognition Interface

Protein-protein interactions are critical determinants in biological systems. Engineered proteins binding to specific areas on protein surfaces could lead to therapeutics or diagnostics for treating diseases in humans. But designing epitope-specific protein-protein interactions with computational atomistic interaction free energy remains a difficult challenge. Here we show that, with the antibody-VEGF (vascular endothelial growth factor) interaction as a model system, the experimentally observed amino acid preferences in the antibody-antigen interface can be rationalized with 3-dimensional distributions of interacting atoms derived from the database of protein structures. Machine learning models established on the rationalization can be generalized to design amino acid preferences in antibody-antigen interfaces, for which the experimental validations are tractable with current high throughput synthetic antibody display technologies. Leave-one-out cross validation on the benchmark system yielded the accuracy, precision, recall (sensitivity) and specificity of the overall binary predictions to be 0.69, 0.45, 0.63, and 0.71 respectively, and the overall Matthews correlation coefficient of the 20 amino acid types in the 24 interface CDR positions was 0.312. The structure-based computational antibody design methodology was further tested with other antibodies binding to VEGF. The results indicate that the methodology could provide alternatives to the current antibody technologies based on animal immune systems in engineering therapeutic and diagnostic antibodies against predetermined antigen epitopes

Snake Cytotoxins Bind to Membranes via Interactions with Phosphatidylserine Head Groups of Lipids

The major representatives of Elapidae snake venom, cytotoxins (CTs), share similar three-fingered fold and exert diverse range of biological activities against various cell types. CT-induced cell death starts from the membrane recognition process, whose molecular details remain unclear. It is known, however, that the presence of anionic lipids in cell membranes is one of the important factors determining CT-membrane binding. In this work, we therefore investigated specific interactions between one of the most abundant of such lipids, phosphatidylserine (PS), and CT 4 of Naja kaouthia using a combined, experimental and modeling, approach. It was shown that incorporation of PS into zwitterionic liposomes greatly increased the membrane-damaging activity of CT 4 measured by the release of the liposome-entrapped calcein fluorescent dye. The CT-induced leakage rate depends on the PS concentration with a maximum at approximately 20% PS. Interestingly, the effects observed for PS were much more pronounced than those measured for another anionic lipid, sulfatide. To delineate the potential PS binding sites on CT 4 and estimate their relative affinities, a series of computer simulations was performed for the systems containing the head group of PS and different spatial models of CT 4 in aqueous solution and in an implicit membrane. This was done using an original hybrid computational protocol implementing docking, Monte Carlo and molecular dynamics simulations. As a result, at least three putative PS-binding sites with different affinities to PS molecule were delineated. Being located in different parts of the CT molecule, these anion-binding sites can potentially facilitate and modulate the multi-step process of the toxin insertion into lipid bilayers. This feature together with the diverse binding affinities of the sites to a wide variety of anionic targets on the membrane surface appears to be functionally meaningful and may adjust CT action against different types of cells

Rapid Sampling of Molecular Motions with Prior Information Constraints

Proteins are active, flexible machines that perform a range of different functions. Innovative experimental approaches may now provide limited partial information about conformational changes along motion pathways of proteins. There is therefore a need for computational approaches that can efficiently incorporate prior information into motion prediction schemes. In this paper, we present PathRover, a general setup designed for the integration of prior information into the motion planning algorithm of rapidly exploring random trees (RRT). Each suggested motion pathway comprises a sequence of low-energy clash-free conformations that satisfy an arbitrary number of prior information constraints. These constraints can be derived from experimental data or from expert intuition about the motion. The incorporation of prior information is very straightforward and significantly narrows down the vast search in the typically high-dimensional conformational space, leading to dramatic reduction in running time. To allow the use of state-of-the-art energy functions and conformational sampling, we have integrated this framework into Rosetta, an accurate protocol for diverse types of structural modeling. The suggested framework can serve as an effective complementary tool for molecular dynamics, Normal Mode Analysis, and other prevalent techniques for predicting motion in proteins. We applied our framework to three different model systems. We show that a limited set of experimentally motivated constraints may effectively bias the simulations toward diverse predicates in an outright fashion, from distance constraints to enforcement of loop closure. In particular, our analysis sheds light on mechanisms of protein domain swapping and on the role of different residues in the motion