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Focus groups were generally the preferred method because this approach allows for interaction among respondents and generates rich data [ 27].
In these efforts, computed tomography has become an important tool when combined with testing of trabecular bone because this approach allows for relating apparent mechanical properties to bone mass and morphology [ 10].
Thus, most of the simulations were performed on genetic distance matrices because this approach allows users to determine, before phylogenetic inference, if the data matrices must be treated in a separate or combined analysis.
For the duration of the 24-hour study period, ventilator settings were periodically adjusted to maintain an arterial pressure of carbon dioxide (pCO2) below BL values because this approach allows invasive ventilation in sheep in the awake state.
Flotation gradient analyses have been successfully used to determine the membrane targeting of RNCs, because this approach allows the differentiation between RNCs that were targeted to the SecYEG-containing membrane fractions of the gradient (fractions 2 and 3) and those that were not targeted or aggregated (fractions 4 and 5) [ 24, 25].
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These efforts can be complemented using machine learning techniques trained on compositional properties in the identification of novel adhesins because in principle, this approach allows development of a non-homology composition based method.
Moreover, because complementation stabilizes the complex, this approach allows one to selectively enrich oligomeric species.
This approach allows flexibility, because it can be scaled to the level of taxonomic/phylogenetic interest (e.g. intraspecies, intragroup, etc)., and it can be adjusted to frequent updates in taxonomy.
Because this approach allowed us to gate anti-Ig or gp41 MPER peptide-ligated B cells, the amount of anti-Ig and gp41 MPER-induced Erk phosphorylation could be compared on a cell-per-cell basis.
To assess the impact of body weight and phospholipid fatty acid concentration on MRS we used General Additive Mixed Models (GAMM), because this approach allowed us to fit smooth curves (penalized cubic regression splines) to the nonlinear relation of MRS to body weight, and to include possible effects of taxonomic relations.
Both ANA and AMA were tested by HEp-2 cell lines for financial constraints and because this approach allowed to obtain information on ANA patterns.
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