976 resultados para Rainer Bruns
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Matrix-assisted laser desorption/ionisation (MALDI) mass spectrometry (MS) is a highly versatile and sensitive analytical technique, which is known for its soft ionisation of biomolecules such as peptides and proteins. Generally, MALDI MS analysis requires little sample preparation, and in some cases like MS profiling it can be automated through the use of robotic liquid-handling systems. For more than a decade now, MALDI MS has been extensively utilised in the search for biomarkers that could aid clinicians in diagnosis, prognosis, and treatment decision making. This review examines the various MALDI-based MS techniques like MS imaging, MS profiling and proteomics in-depth analysis where MALDI MS follows fractionation and separation methods such as gel electrophoresis, and how these have contributed to prostate cancer biomarker research. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.
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NDIR is proposed for monitoring of air pollutants emitted by ship engines. Careful optical filtering overcomes the challenge of optical detection of NO2 in humid exhaust gas, despite spectroscopic overlap with the water vapour band.
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In this EUDO CITIZENSHIP Forum Debate, several authors consider the interrelations between eligibility criteria for participation in independence referendum (that may result in the creation of a new independent state) and the determination of putative citizenship ab initio (on day one) of such a state. The kick-off contribution argues for resemblance of an independence referendum franchise and of the initial determination of the citizenry, critically appraising the incongruence between the franchise for the 18 September 2014 Scottish independence referendum, and the blueprint for Scottish citizenship ab initio put forward by the Scottish Government in its 'Scotland's Future' White Paper. Contributors to this debate come from divergent disciplines (law, political science, sociology, philosophy). They reflect on and contest the above claims, both generally and in relation to regional settings including (in addition to Scotland) Catalonia/Spain, Flanders/Belgium, Quebec/Canada, Post-Yugoslavia and Puerto-Rico/USA.
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The concept of rationally designing MALDI matrices has been extended to the next “whole sample” level. These studies have revealed some unexpected and exploitable insights in improving MALDI sensitivity. It is shown that (i) additives which only provide additional laser energy absorption are best to be avoided; (ii) the addition of proton donors in the form of protonated weak bases can be highly beneficial; (iii) the addition of glycerol for coating crystalline samples is highly recommended. Overall, analytical sensitivity has been significantly increased compared to the current “gold” standards in MALDI MS, and new insights into the mechanisms and processes of MALDI have been gained.
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Evidence is presented that the performance of the rationally designed MALDI matrix 4-chloro-α-cyanocinnamic acid (ClCCA) in comparison to its well-established predecessor α-cyano-4-hydroxycinnamic acid (CHCA) is significantly dependent on the sample preparation, such as the choice of the target plate. In this context, it becomes clear that any rational designs of MALDI matrices and their successful employment have to consider a larger set of physicochemical parameters, including sample crystallization and morphology/topology, in addition to parameters of basic (solution and/or gas-phase) chemistry.
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Background: MS-based proteomics was applied to the analysis of the medicinal plant Artemisia annua, exploiting a recently published contig sequence database (Graham et al. (2010) Science 327, 328–331) and other genomic and proteomic sequence databases for comparison. A. annua is the predominant natural source of artemisinin, the precursor for artemisinin-based combination therapies (ACTs), which are the WHO-recommended treatment for P. falciparum malaria. Results: The comparison of various databases containing A. annua sequences (NCBInr/viridiplantae, UniProt/ viridiplantae, UniProt/A. annua, an A. annua trichome Trinity contig database, the above contig database and another A. annua EST database) revealed significant differences in respect of their suitability for proteomic analysis, showing that an organism-specific database that has undergone extensive curation, leading to longer contig sequences, can greatly increase the number of true positive protein identifications, while reducing the number of false positives. Compared to previously published data an order-of-magnitude more proteins have been identified from trichome-enriched A. annua samples, including proteins which are known to be involved in the biosynthesis of artemisinin, as well as other highly abundant proteins, which suggest additional enzymatic processes occurring within the trichomes that are important for the biosynthesis of artemisinin. Conclusions: The newly gained information allows for the possibility of an enzymatic pathway, utilizing peroxidases, for the less well understood final stages of artemisinin’s biosynthesis, as an alternative to the known non-enzymatic in vitro conversion of dihydroartemisinic acid to artemisinin. Data are available via ProteomeXchange with identifier PXD000703.
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Rainer Maria Rilke (1875-1926) is universally recognized as among the most important twentieth-century German-language poets. Here, for the first time, are all the surviving translations of his poetry made by Ruth Speirs (1916-2000), a Latvian exile who joined the British literary community in Cairo during World War Two, becoming a close friend of Lawrence Durrell and Bernard Spencer. Though described as ‘excellent’ and ‘the best’ by J. M. Cohen on the basis of magazine and anthology appearances, copyright restrictions meant that during her lifetime, with the exception of a Cairo-published Selected Poems (1942), Speirs was never to see her work gathered between covers and in print. This volume, edited by John Pilling and Peter Robinson, brings Speirs’ translations the belated recognition they deserve. Her much-revised and considered versions are a key document in the history of Rilke’s Anglophone dissemination. Rhythmically alive and carefully faithful, they give a uniquely mid-century English accent to the poet’s extraordinary German, and continue to bear comparison with current efforts to render his tenderly taxing voice.
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This paper explores the concept of a reverse diffusion of knowledge, that is, the transfer flowing from a company’s subsidiary to its home plant. The article presents the empirical evidence gathered in General Motors UK and Poland, where the reverse diffusion of a concept of the built-in quality took place. Lastly, the implications of our findings for future research are discussed.
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MS-based proteomic methods were utilised for the first time in the discovery of novel penile cancer biomarkers. MALDI MS imaging was used to obtain the in situ biomolecular MS profile of squamous cell carcinoma of the penis which was then compared to benign epithelial MS profiles. Spectra from cancerous and benign tissue areas were examined to identify MS peaks that best distinguished normal epithelial cells from invasive squamous epithelial cells, providing crucial evidence to suggest S100A4 to be differentially expressed. Verification by immunohistochemistry resulted in positive staining for S100A4 in a sub-population of invasive but not benign epithelial cells.
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This paper describes the methodology of providing multiprobability predictions for proteomic mass spectrometry data. The methodology is based on a newly developed machine learning framework called Venn machines. Is allows to output a valid probability interval. The methodology is designed for mass spectrometry data. For demonstrative purposes, we applied this methodology to MALDI-TOF data sets in order to predict the diagnosis of heart disease and early diagnoses of ovarian cancer and breast cancer. The experiments showed that probability intervals are narrow, that is, the output of the multiprobability predictor is similar to a single probability distribution. In addition, probability intervals produced for heart disease and ovarian cancer data were more accurate than the output of corresponding probability predictor. When Venn machines were forced to make point predictions, the accuracy of such predictions is for the most data better than the accuracy of the underlying algorithm that outputs single probability distribution of a label. Application of this methodology to MALDI-TOF data sets empirically demonstrates the validity. The accuracy of the proposed method on ovarian cancer data rises from 66.7 % 11 months in advance of the moment of diagnosis to up to 90.2 % at the moment of diagnosis. The same approach has been applied to heart disease data without time dependency, although the achieved accuracy was not as high (up to 69.9 %). The methodology allowed us to confirm mass spectrometry peaks previously identified as carrying statistically significant information for discrimination between controls and cases.