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2 results for “microflow”
Yeast proteomics microflow 23 min gradient DIA-MS
<p><em>Saccharomyces cerevisiae</em> (BY4743 rendered prototrophic with a plasmid encoding for HIS3, LEU2 and URA3 <a href="https://paperpile.com/c/AXHME6/nwrF">[25]</a>) were grown to exponential phase in minimal synthetic nutrient media. Proteins were extracted by bead beating for 5min at 1500rpm in 8M urea/0.1M ammonium bicarbonate. Proteins were reduced with 5mM dithiothreitol, alkylated with 10mM iodoacetamide. The sample was diluted to 1.5M urea/0.1M ammonium bicarbonate before the proteins were digested overnight with Trypsin (1:30 Trypsin to total protein ratio). Peptides were cleaned-up with 96-well MacroSpin plates (Nest Group) and iRT peptides (Biognosys AG) were spiked in.</p> <p>The digested peptides were analysed on a nanoAcquity (Waters) coupled to a TripleTOF 6600 (Sciex). Peptides were separated with a 23 minute non-linear gradient (4% Acetonitrile/0.1 % formic acid to 36% Acetonitrile/0.1% formic acid) on a Waters HSS T3 column (150mm x 300μm, 1.8μm Particles) with a 5μl/min flow rate. The DIA method consisted of an MS1 scan from m/z 400 to m/z 1250 (50ms accumulation time) and 40 MS2 scans (35ms accumulation time) with variable precursor isolation width covering the mass range from m/z 400 to m/z 1250.</p>
EMUE-D5-5-Microflow
<p>The objective of this study was to compare uncertainty evaluation methodologies for very small flow rates, close to zero, during calibration. To exemplify the mathematical treatment of the uncertainty evaluation, experimental values arising from a syringe pump calibration were used to assess the viability and advantage of using alternative methods to the traditional GUM approach (law of propagation of uncertainty), namely, Monte Carlo and Bayesian methods, to quantify measurement uncertainty when the conditions for the applicability of the GUM uncertainty framework are not met. Such conditions relate to the extent of the non-linearity of the model, the number and magnitude of quantities with non-normal distributions and the ability to produce meaningful results for a specific application. Validation should always be attempted whenever the application of the GUM is questionable.</p> <p>Files contained in the dataset are:</p> <ul> <li>A2.3.4 Microflow.pdf: Report “Uncertainty calculation methodologies in microflow measurements: comparison of GUM, GUM-S1 and Bayesian approach”</li> <li>Case 1.xls: Excel spreadsheet containing the data associated with case study 1.</li> <li>Case 2.xls: Excel spreadsheet containing the data associated with case study 2.</li> </ul>
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