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This resulted in much smaller variations in counts for any one sample, which allowed us to examine the growth of these cells after being treated by MB and/or NC solutions under UV excitation.
Investigations have been performed in the bulk of the sample, which allowed to study local distribution of the chemical composition through the thickness of the BFO film, LSCO layer, and part of the substrate.
A median of 16,016 (range 2,406 35,401) sequence reads were obtained per sample, which allowed detection and quantification of minority resistance mutations at amino acid position 181, 184, 188, 190, 210, 215 and 219 in RT.
An internal standard approach was taken, using a pool of equal protein amounts of each sample, which allowed for the inter-comparison of the six gels.
Using deep-sequencing technology, they obtained a whole genome sequence of C. albicans from each sample, which allowed them to produce a comprehensive catalogue of the different genetic variants of the fungus.
We added a spike-in of non-human control RNA to each sample, which allowed us to confirm the effects of RNA degradation on the RNA sequencing results (see Methods for more details).
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In the proposed technique the heat energy source and IR detector are located at the same side of the investigated sample, which allows taking into account the finite dimension, as well as real shape of the sample.
Up to 100 different species can be identified simultaneously in a single sample, which allows for additional use of this method in community analyses extended to all phytoplankton species.
MAEB serves as the maximum number of attempt of re-transmission of erroneous data per sample which allows the maximum transmission period to be known and guaranteed for time-critical control system.
The strengths of this study include the analysis of a longitudinal sample, which allows inferring data on child development along different stages, although not causal relationships.
First, only 1-dimensional probability densities are considered because the density is always only evaluated for a single test sample, which allows a 1-dimensional embedding of the feature space defined by the kernel and two data points (the support vector and the test sample).
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