Analysis of Heat Flux Distribution during Brush Seal Rubbing Using CFD with Porous Media Approach

This paper discusses the question of heat flux distribution between bristle package and rotor during a rubbing event. A three-dimensional Computational Fluid Dynamics (3D CFD) model of the brush seal test rig installed at the Institute of Thermal Turbomachinery (ITS) was created. The bristle package is modelled as a porous medium with local non-thermal equilibrium. The model is used to numerically recalculate experimentally conducted rub tests on the ITS test rig. The experimentally determined total frictional power loss serves as an input parameter to the numerical calculation. By means of statistical evaluation methods, the ma in influences on the heat flux distribution and the maximum temperature in the frictional contact are determined. The heat conductivity of the rotor material, the heat transfer coefficients at the bristles and the rubbing surface were identified as the dominant factors

Efficient Interpretation of Tandem Mass Tags in Top-Down Proteomics

Mass spectrometry is the major analytical tool for the identification and quantification of proteins in biological samples. In so-called top-down proteomics, separation and mass spectrometric analysis is performed at the level of intact proteins, without preparatory digestion steps. It has been shown that the tandem mass tag (TMT) labeling technology, which is often used for quantification based on digested proteins (bottom-up studies), can be applied in top-down proteomics as well. This, however, leads to a complex interpretation problem, where we need to annotate measured peaks with their respective generating protein, the number of charges, and the a priori unknown number of TMT-groups attached to this protein. In this work, we give an algorithm for the efficient enumeration of all valid annotations that fulfill available experimental constraints. Applying the algorithm to real-world data, we show that the annotation problem can indeed be efficiently solved. However, our experiments also demonstrate that reliable annotation in complex mixtures requires at least partial sequence information and high mass accuracy and resolution to go beyond the proof-of-concept stage

Time-Resolved Analysis of a Highly Sensitive Förster Resonance Energy Transfer Immunoassay Using Terbium Complexes as Donors and Quantum Dots as Acceptors

CdSe/ZnS core/shell quantum dots (QDs) are used as efficient Förster Resonance Energy Transfer (FRET) acceptors in a time-resolved immunoassays with Tb complexes as donors providing a long-lived luminescence decay. A detailed decay time analysis of the FRET process is presented. QD FRET sensitization is evidenced by a more than 1000-fold increase of the QD luminescence decay time reaching ca. 0.5 milliseconds, the same value to which the Tb donor decay time is quenched due to FRET to the QD acceptors. The FRET system has an extremely large Förster radius of approx. 100 Å and more than 70% FRET efficiency with a mean donor-acceptor distance of ca. 84 Å, confirming the applied biotin-streptavidin binding system. Time-resolved measurement allows for suppression of short-lived emission due to background fluorescence and directly excited QDs. By this means a detection limit of 18 attomol QDs within the immunoassay is accomplished, an improvement of more than two orders of magnitude compared to commercial systems

NightShift: NMR shift inference by general hybrid model training - a framework for NMR chemical shift prediction

BACKGROUND: NMR chemical shift prediction plays an important role in various applications in computational biology. Among others, structure determination, structure optimization, and the scoring of docking results can profit from efficient and accurate chemical shift estimation from a three-dimensional model. A variety of NMR chemical shift prediction approaches have been presented in the past, but nearly all of these rely on laborious manual data set preparation and the training itself is not automatized, making retraining the model, e.g., if new data is made available, or testing new models a time-consuming manual chore. RESULTS: In this work, we present the framework NightShift (NMR Shift Inference by General Hybrid Model Training), which enables automated data set generation as well as model training and evaluation of protein NMR chemical shift prediction. In addition to this main result – the NightShift framework itself – we describe the resulting, automatically generated, data set and, as a proof-of-concept, a random forest model called Spinster that was built using the pipeline. CONCLUSION: By demonstrating that the performance of the automatically generated predictors is at least en par with the state of the art, we conclude that automated data set and predictor generation is well-suited for the design of NMR chemical shift estimators. The framework can be downloaded from https://bitbucket.org/akdehof/nightshift. It requires the open source Biochemical Algorithms Library (BALL), and is available under the conditions of the GNU Lesser General Public License (LGPL). We additionally offer a browser-based user interface to our NightShift instance employing the Galaxy framework via https://ballaxy.bioinf.uni-sb.de/

Composition and Stability of the Oxidative Phosphorylation System in the Halophile Plant Cakile maritima

Mitochondria play a central role in the energy metabolism of plants. At the same time, they provide energy for plant stress responses. We here report a first view on the mitochondrial Oxidative Phosphorylation (OXPHOS) system of the halophile (salt tolerant) plant Cakile maritima. Mitochondria were purified from suspension cultures of C. maritima and for comparison of Arabidopsis thaliana, a closely related glycophyte (salt sensitive) plant. Mitochondria were treated with digitonin and solubilized protein complexes were analyzed by 2D Blue native/SDS polyacrylamide gel electrophoresis. The OXPHOS systems of the two compared plants exhibit some distinct differences. C. maritima mitochondria include a very abundant respiratory supercomplex composed of monomeric complex I and dimeric complex III. At the same time the complexes II and IV are of reduced abundance. The stability of the OXPHOS complexes was investigated by combined salt and temperature treatments of isolated mitochondria. ATP synthase (complex V) is of increased stability in C. maritima. Also, the I + III2 supercomplex is present in high abundance during stress treatments. These results give insights into the mitochondrial contribution to the plant salt stress response

Synergistic influence of phosphorylation and metal ions on tau oligomer formation and coaggregation with alpha-synuclein at the single molecule level

Background: Fibrillar amyloid-like deposits and co-deposits of tau and alpha-synuclein are found in several common neurodegenerative diseases. Recent evidence indicates that small oligomers are the most relevant toxic aggregate species. While tau fibril formation is well-characterized, factors influencing tau oligomerization and molecular interactions of tau and alpha-synuclein are not well understood. Results: We used a novel approach applying confocal single-particle fluorescence to investigate the influence of tau phosphorylation and metal ions on tau oligomer formation and its coaggregation with alpha-synuclein at the level of individual oligomers. We show that Al3+ at physiologically relevant concentrations and tau phosphorylation by GSK-3 beta exert synergistic effects on the formation of a distinct SDS-resistant tau oligomer species even at nanomolar protein concentration. Moreover, tau phosphorylation and Al3+ as well as Fe3+ enhanced both formation of mixed oligomers and recruitment of alpha-synuclein in pre-formed tau oligomers. Conclusions: Our findings provide a new perspective on interactions of tau phosphorylation, metal ions, and the formation of potentially toxic oligomer species, and elucidate molecular crosstalks between different aggregation pathways involved in neurodegeneration

A minimally invasive multiple marker approach allows highly efficient detection of meningioma tumors

BACKGROUND: The development of effective frameworks that permit an accurate diagnosis of tumors, especially in their early stages, remains a grand challenge in the field of bioinformatics. Our approach uses statistical learning techniques applied to multiple antigen tumor antigen markers utilizing the immune system as a very sensitive marker of molecular pathological processes. For validation purposes we choose the intracranial meningioma tumors as model system since they occur very frequently, are mostly benign, and are genetically stable. RESULTS: A total of 183 blood samples from 93 meningioma patients (WHO stages I-III) and 90 healthy controls were screened for seroreactivity with a set of 57 meningioma-associated antigens. We tested several established statistical learning methods on the resulting reactivity patterns using 10-fold cross validation. The best performance was achieved by Naïve Bayes Classifiers. With this classification method, our framework, called Minimally Invasive Multiple Marker (MIMM) approach, yielded a specificity of 96.2%, a sensitivity of 84.5%, and an accuracy of 90.3%, the respective area under the ROC curve was 0.957. Detailed analysis revealed that prediction performs particularly well on low-grade (WHO I) tumors, consistent with our goal of early stage tumor detection. For these tumors the best classification result with a specificity of 97.5%, a sensitivity of 91.3%, an accuracy of 95.6%, and an area under the ROC curve of 0.971 was achieved using a set of 12 antigen markers only. This antigen set was detected by a subset selection method based on Mutual Information. Remarkably, our study proves that the inclusion of non-specific antigens, detected not only in tumor but also in normal sera, increases the performance significantly, since non-specific antigens contribute additional diagnostic information. CONCLUSION: Our approach offers the possibility to screen members of risk groups as a matter of routine such that tumors hopefully can be diagnosed immediately after their genesis. The early detection will finally result in a higher cure- and lower morbidity-rate