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RNA isolation and characterization Total RNA was
Depending on the characteristics of the ligands we observed that linear and non-linear fitting gave significantly different solutions when very strong ligands were present (Table 1). Linear fitting gave estimations of [LS] and log K′S much closer to [L1] and log K′L1 ([LS] = 1.7 × [L1]) than non-linear fitting for both SITE,non and SFIT(5) (where [LS] ~ 4 × [L1]). This is due to the limited use for the calculation of [LS] and K′S, of those initial data in which the metal is mostly complexed by L1 as opposed to the combined use of all data during non-linear fitting. As a result, linear fitting better resolved those ligands with very high LDK378 constants getting [LS] and K′S values closer to [L1] and K′L1 and what it is more important, a better pCu (99.8% compared to 97.9%). Surprisingly, feeding of the non-linear routine with the preset S did not improve the estimation of pCu. Non-linear fitting gave estimations of LW and K′W closer to L3 and K′L3. That difference could suggest that the definition of the upper limit of the analytical window could also depend on the fitting method selected and not just on the accuracy of the analytical procedure as pointed out before (Apte et al., 198 cool . This possible redefinition should be addressed in future work as pseudocoelomates would change our understanding of the analytical window. The fixing of S to its real value during non-linear fitting gave results that did not differ significantly from those found using SITE,non or SFIT(5).





 
 
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