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The luminex microsphere system allows for the detection of many cytokines and chemokines in a single sample, but the detection method of using aligned lasers and fluidics means that samples often have to be analysed in low containment facilities.
In addition, the forms of the solid samples often have strong effect on the optical properties of the material [22].
Theoretical studies usually predict higher mechanical strength since they assume a perfect crystalline structure while experimentally synthesized samples often have defects and grain boundaries [21].
Unfortunately, reads sequenced from these types of samples often have a heterogeneous mix of various subpopulations with different variants, making assembly extremely difficult using existing assembly tools.
Indeed biological samples often have different numbers of transcribed genes/transcripts, different degree of transcriptome complexity and a dynamic distribution of expression levels for transcripts all of which can make data interpretation quite challenging.
Furthermore, OCT (FFOCM) images of biomedical samples often have to be compared to gold standards, like histology or fluorescence imaging, in order to establish and validate the contents of the reflectance image.
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However, the search for an optimal and small subset of genes that has a high discriminatory power in classifying field samples often having multiple classes is much more complicated.
Although MALDI MS is capable of profiling small samples for qualitative information, adding labeling reagents, performing reactions, and mixing control and experimental samples often has limited the application of stable isotope labeling to many-fold larger samples.
If we keep in mind that the pre-Fukushima samples often had Sr/Cs activity ratios > 2 (up to 10), this scenario illustrates the potentially severe impact of this erroneous assumption of a constant ratio at 0.1 (or even below).
Additionally, studies of this type in which revision patients must agree to frequent blood sampling often have a high attrition rate, which limits the number of cases analyzed.
Also, a sample often has to represent different levels (e.g. regions, ECEC providers, ECEC settings, groups and children, e.g. Anders et al. 2016; Bird et al. 2016; Weinert et al. 2016) and make sure that the relevant subgroups (e.g. ethnic groups, e.g. Bird et al. 2016; Weinert et al. 2016) are large enough to draw comparisons to other subgroups.
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CEO of Professional Science Editing for Scientists @ prosciediting.com