Human serum transferrin consists of two iron-binding lobes connected by a short peptide linker. While the high homology and structural similarity between the two halves of the molecule would suggest similar characteristics, it has been shown that the pH-dependent rate of release of iron from the N-terminal lobe is quite different from that of its C-terminal counterpart. This suggests that the N-lobe of human serum transferrin has a specific, pH-dependent, molecular mechanism for releasing iron. Sacchettini and co-workers using structural information have hypothesized that two lysines in the N-terminal lobe of ovotransferrin create a dilysine interaction and suggest that this is the trigger for pH-dependent iron release. To investigate this hypothesis, we used a Pichia pastoris expression system to produce large amounts of wild-type nTf, the single point mutants, nTfK206A (Lys 206 to alanine) and nTfK296A (Lys 296 to alanine), and the double mutant, nTfK206/296A. The purified recombinant proteins were then used to measure rates of iron release to pyrophosphate. It was found that the rate of iron release from all three mutant proteins at pH 5.7 (the pH at which nTf would normally release iron) was too slow to measure. Only when the pH was reduced to 5.0 could the rates of iron release from the mutant proteins be reliably determined. Although this precludes a direct comparison to wild-type nTf (the rate of iron release from nTf at pH 5.0 is too fast to measure), it implicates lysines 206 and 296 in the pH-dependent release of iron from nTf.
The purpose of this paper is to investigate the use of fractal dimensions in the characterization of chaotic systems in structural dynamics. The investigation focuses on the example of a simply-supported, Euler-Bernoulli beam which when subjected to a transverse forcing function of a particular amplitude responds chaotically. Three different nonlinear models of the system are studied: a complex partial differential equation (PDE) model, a simplified PDE model, and a Galerkin approximation to the simpler PDE model. The responses of each model are examined through zero velocity Poincare´ sections. To characterize and compare the chaotic trajectories, the box counting fractal dimension of the Poincare´ sections are computed. The results demonstrate that the fractal dimension is a spatial invariant along the length of the beam for the specific class of forcing function studied, and thus it can be used to characterize chaotic motions. In addition, the three models yield different fractal dimensions for the same forcing which indicates that fractal dimensions can also be used to quantify whether a simplification of a chaotic model accurately predicts the chaotic behavior of the full-blown model. Thus the conclusion of the paper is that fractal dimensions may play an important role in the characterization of chaotic structural dynamic systems.
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