80 resultados para liquid-liquid equilibrium
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Video performance with Live Sounds, Szuper Gallery (solo)
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Video Performance with Live Sound, Institute of Contemporary Art, London, (solo)
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Although liquid matrix-assisted laser desorption/ionization (MALDI) has been used in mass spectrometry (MS) since the early introduction of MALDI, its substantial lack of sensitivity compared to solid (crystalline) MALDI was for a long time a major hurdle to its analytical competitiveness. In the last decade, this situation has changed with the development of new sensitive liquid matrices, which are often based on a binary matrix acid/base system. Some of these matrices were inspired by the recent progress in ionic liquid research, while others were developed from revisiting previous liquid MALDI work as well as from a combination of these two approaches. As a result, two high-performing liquid matrix classes have been developed, the ionic liquid matrices (ILMs) and the liquid support matrices (LSMs), now allowing MS measurements at a sensitivity level that is very close to the level of solid MALDI and in some cases even surpasses it. This chapter provides some basic information on a selection of highly successful representatives of these new liquid matrices and describes in detail how they are made and applied in MALDI MS analysis.
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Matrix-assisted laser desorption/ionisation (MALDI) coupled with time-of-flight (TOF) mass spectrometry (MS) is a powerful tool for the analysis of biological samples, and nanoflow high-performance liquid chromatography (nanoHPLC) is a useful separation technique for the analysis of complex proteomics samples. The off-line combination of MALDI and nanoHPLC has been extensively investigated and straightforward techniques have been developed, focussing particularly on automated MALDI sample preparation that yields sensitive and reproducible spectra. Normally conventional solid MALDI matrices such as α-cyano-4-hydroxycinnamic acid (CHCA) are used for sample preparation. However, they have limited usefulness in quantitative measurements and automated data acquisition because of the formation of heterogeneous crystals, resulting in highly variable ion yields and desorption/ ionization characteristics. Glycerol-based liquid support matrices (LSM) have been proposed as an alternative to the traditional solid matrices as they provide increased shot-to-shot reproducibility, leading to prolonged and stable ion signals and therefore better results. This chapter focuses on the integration of the liquid LSM MALDI matrices into the LC-MALDI MS/MS approach in identifying complex and large proteomes. The interface between LC and MALDI consists of a robotic spotter, which fractionates the eluent from the LC column into nanoliter volumes, and co-spots simultaneously the liquid matrix with the eluent fractions onto a MALDI target plate via sheath flow. The efficiency of this method is demonstrated through the analysis of trypsin digests of both bovine serum albumin (BSA) and Lactobacillus plantarum WCFS1 proteins.
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The Southern Ocean is a critical region for global climate, yet large cloud and solar radiation biases over the Southern Ocean are a long-standing problem in climate models and are poorly understood, leading to biases in simulated sea surface temperatures. This study shows that supercooled liquid clouds are central to understanding and simulating the Southern Ocean environment. A combination of satellite observational data and detailed radiative transfer calculations is used to quantify the impact of cloud phase and cloud vertical structure on the reflected solar radiation in the Southern Hemisphere summer. It is found that clouds with supercooled liquid tops dominate the population of liquid clouds. The observations show that clouds with supercooled liquid tops contribute between 27% and 38% to the total reflected solar radiation between 40° and 70°S, and climate models are found to poorly simulate these clouds. The results quantify the importance of supercooled liquid clouds in the Southern Ocean environment and highlight the need to improve understanding of the physical processes that control these clouds in order to improve their simulation in numerical models. This is not only important for improving the simulation of present-day climate and climate variability, but also relevant for increasing confidence in climate feedback processes and future climate projections.