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To minimize sample loss during purification, we optimized the experimental procedure and avoided unnecessary purification steps.
Figure 1 displays the recommended pipeline structure, designed to optimize the QC and minimize sample loss.
To minimize sample loss, anthropometric measurements were taken on two different occasions in each school at both time-points.
One solution is to directly couple sample processing with nanoflow LC-MS in order to minimize sample loss and increase detection sensitivity.
Fourth, modifications to the sample inlet and pressure source had to be made to facilitate sample loading and minimize sample loss in the inlet.
Increased detectability of targets should be addressed in the future by targeting alternative peptides, further optimizing procedures to minimize sample loss and utilizing alternative investigative devices, including both more sensitive mass spectrometers and digital immunoassays.
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Additionally, by using a procedure that minimizes sample loss and contamination, we were able to achieve a greater degree of validation compared to conventional procedures, as judged by the detection of the corresponding protein-encoding transcripts in whole blastocysts.
The sample was spread onto 8 SuperFrost® Plus slides (VWR) by pipetting 150 uL of the mixture onto a slide resting in a manual spreading device (CyteSpreader®, RareCyte) that was designed to evenly distribute the sample in a monolayer across a defined region of the slide without making contact with the slide and thus minimizing sample loss (see Figure 2).
We then developed a workflow for single muscle fiber proteome analysis on the basis of a recent method, in which all preparation steps subsequent to mechanical disruption are performed in a single vessel, thereby minimizing sample loss (Fig 1A and Supplementary Methods section) [ 19].
Incorporation of a sample pump flush minimizes sample loss and enables recoveries ranging from the low tens of micrograms to milligram quantities of protein.
The single immunoprecipitation approach minimizes sample loss, a common problem in TAP methods.
More suggestions(15)
minimize energy loss
minimize sample degradation
minimize information loss
minimize blood loss
minimize participant loss
minimize sample set
minimize sample heterogeneity
minimize sample variance
minimize material loss
minimize memory loss
minimize sample consumption
minimize product loss
minimize sample carry-over
minimize sample charging
minimize sample handling
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