Folding minimal sequences: the lower bound for sequence complexity of globular proteins.
(17/1338)
Alphabet size and informational entropy, two formal measures of sequence complexity, are herein applied to two prior studies on the folding of minimal proteins. These measures show a designed four-helix bundle to be unlike its natural counterparts but rather more like a coiled-coil dimer. Segments from a simplified sarc homology 3 domain and more than 2000000 segments from globular proteins both have lower bounds for alphabet size of 10 and for entropy near 2.9. These values are therefore suggested to be necessary and sufficient for folding into globular proteins having both rigid side chain packing and biological function. (+info)
Decreased RR interval complexity and loss of circadian rhythm in patients with congestive heart failure.
(18/1338)
The present study investigated how the RR interval complexity and variability and their circadian rhythms alter for patients with congestive heart failure (CHF). Sixteen patients aged between 41 and 72 years with CHF and 20 control subjects were included. 24-h ambulatory electrocardiographic recordings were analyzed, and digitized data was partitioned into sections of 30-min duration. For each section, time- and frequency-domain indices, and complexity indices of heart rate variability were calculated. For CHF patients, 24-h average values of all indices were significantly decreased. The circadian rhythms of mean RR intervals were preserved and resembled the abnormal circadian rhythms of the low-frequency power. The circadian rhythms of high-frequency power and all complexity indices shown in the normal control were lost. Conclusively, the patients with CHF showed decreased RR interval complexity and loss of its circadian rhythm, in addition to decreased frequency-domain RR interval variability and its abnormal circadian rhythm. (+info)
Theoretical neuroanatomy: relating anatomical and functional connectivity in graphs and cortical connection matrices.
(19/1338)
Neuroanatomy places critical constraints on the functional connectivity of the cerebral cortex. To analyze these constraints we have examined the relationship between structural features of networks (expressed as graphs) and the patterns of functional connectivity to which they give rise when implemented as dynamical systems. We selected among structurally varying graphs using as selective criteria a number of global information-theoretical measures that characterize functional connectivity. We selected graphs separately for increases in measures of entropy (capturing statistical independence of graph elements), integration (capturing their statistical dependence) and complexity (capturing the interplay between their functional segregation and integration). We found that dynamics with high complexity were supported by graphs whose units were organized into densely linked groups that were sparsely and reciprocally interconnected. Connection matrices based on actual neuroanatomical data describing areas and pathways of the macaque visual cortex and the cat cortex showed structural characteristics that coincided best with those of such complex graphs, revealing the presence of distinct but interconnected anatomical groupings of areas. Moreover, when implemented as dynamical systems, these cortical connection matrices generated functional connectivity with high complexity, characterized by the presence of highly coherent functional clusters. We also found that selection of graphs as they responded to input or produced output led to increases in the complexity of their dynamics. We hypothesize that adaptation to rich sensory environments and motor demands requires complex dynamics and that these dynamics are supported by neuroanatomical motifs that are characteristic of the cerebral cortex. (+info)
Conscious and unconscious processing of nonverbal predictability in Wernicke's area.
(20/1338)
The association of nonverbal predictability and brain activation was examined using functional magnetic resonance imaging in humans. Participants regarded four squares displayed horizontally across a screen and counted the incidence of a particular color. A repeating spatial sequence with varying levels of predictability was embedded within a random color presentation. Both Wernicke's area and its right homolog displayed a negative correlation with temporal predictability, and this effect was independent of individuals' conscious awareness of the sequence. When individuals were made aware of the underlying sequential predictability, a widespread network of cortical regions displayed activity that correlated with the predictability. Conscious processing of predictability resulted in a positive correlation to activity in right prefrontal cortex but a negative correlation in posterior parietal cortex. These results suggest that conscious processing of predictability invokes a large-scale cortical network, but independently of awareness, Wernicke's area processes predictive events in time and may not be exclusively associated with language. (+info)
High-frequency oscillations in circulating amylin concentrations in healthy humans.
(21/1338)
Amylin is stored in the pancreatic beta-cell granules and cosecreted with insulin in response to nutrient stimuli. To gain further insight into control of hormonal release in beta-cell physiology, we examined whether amylin, like insulin, circulates in a high-frequency oscillatory pattern, and if it does, to compare the secretory patterns of the two hormones. Eight overnight-fasted healthy individuals were studied during intravenous glucose infusion (2.0 mg. kg(-1). min(-1)). Blood was collected every minute for 90 min and analyzed in triplicate for amylin, total amylin immunoreactivity (TAI), and insulin. Mean plasma concentrations of amylin (nonglycosylated), TAI (nonglycosylated plus glycosylated), insulin, and glucose were 2.77 +/- 1.21 pmol/l, 7.60 +/- 1.73 pmol/l, 50.4 +/- 17.5 pmol/l, and 5.9 +/- 0.3 mmol/l, respectively. The 90-min time series of amylin, TAI, and insulin were analyzed for periodicity (by spectral analysis, autocorrelation analysis, and deconvolution analysis) and regularity [by approximate entropy (ApEn)]. Significant spectral density peaks were demonstrated by a random shuffling technique in 7 (out of 7), 8 (out of 8), and 8 (out of 8) time series, respectively, whereas autocorrelation analysis revealed significant pulsatility in 5 (out of 7), 7 (out of 8), and 5 (out of 8), respectively. The dominant periodicity of oscillations determined by spectral analysis was 4.6 +/- 0.3, 4.6 +/- 0.4, and 6. 5 +/- 1.1 min/pulse, respectively (amylin vs. insulin, P = 0.017, TAI vs. insulin, P = 0.018). By deconvolution analysis, amylin and insulin periodicities were, respectively, 6.3 +/- 1.0 and 5.5 +/- 0. 6 min. By application of the regularity statistic, ApEn, 6 (out of 7), 7 (out of 8), and 6 (out of 8), respectively, were found to be significantly different from random. In conclusion, like several other hormones, circulating amylin concentrations exhibit oscillations in the secretory patterns for nonglycosylated as well as glycosylated forms. Whether the high-frequency pulsatile release of amylin is disturbed in diabetes is not known. (+info)
Structure-based thermodynamic analysis of the dissociation of protein phosphatase-1 catalytic subunit and microcystin-LR docked complexes.
(22/1338)
The relationship between the structure of a free ligand in solution and the structure of its bound form in a complex is of great importance to the understanding of the energetics and mechanism of molecular recognition and complex formation. In this study, we use a structure-based thermodynamic approach to study the dissociation of the complex between the toxin microcystin-LR (MLR) and the catalytic domain of protein phosphatase-1 (PP-1c) for which the crystal structure of the complex is known. We have calculated the thermodynamic parameters (enthalpy, entropy, heat capacity, and free energy) for the dissociation of the complex from its X-ray structure and found the calculated dissociation constant (4.0 x 10(-11)) to be in excellent agreement with the reported inhibitory constant (3.9 x 10(-11)). We have also calculated the thermodynamic parameters for the dissociation of 47 PP-1c:MLR complexes generated by docking an ensemble of NMR solution structures of MLR onto the crystal structure of PP-1c. In general, we observe that the lower the root-mean-square deviation (RMSD) of the docked complex (compared to the X-ray complex) the closer its free energy of dissociation (deltaGd(o)) is to that calculated from the X-ray complex. On the other hand, we note a significant scatter between the deltaGd(o) and the RMSD of the docked complexes. We have identified a group of seven docked complexes with deltaGd(o) values very close to the one calculated from the X-ray complex but with significantly dissimilar structures. The analysis of the corresponding enthalpy and entropy of dissociation shows a compensation effect suggesting that MLR molecules with significant structural variability can bind PP-1c and that substantial conformational flexibility in the PP-1c:MLR complex may exist in solution. (+info)
Contribution of proton linkage to the thermodynamic stability of the major cold-shock protein of Escherichia coli CspA.
(23/1338)
The stability of protein is defined not only by the hydrogen bonding, hydrophobic effect, van der Waals interactions, and salt bridges. Additional, much more subtle contributions to protein stability can arise from surface residues that change their properties upon unfolding. The recombinant major cold shock protein of Escherichia coli CspA an all-beta protein unfolds reversible in a two-state manner, and behaves in all other respects as typical globular protein. However, the enthalpy of CspA unfolding strongly depends on the pH and buffer composition. Detailed analysis of the unfolding enthalpies as a function of pH and buffers with different heats of ionization shows that CspA unfolding in the pH range 5.5-9.0 is linked to protonation of an amino group. This amino group appears to be the N-terminal alpha-amino group of the CspA molecule. It undergoes a 1.6 U shift in pKa values between native and unfolded states. Although this shift in pKa is expected to contribute approximately 5 kJ/mol to CspA stabilization energy the experimentally observed stabilization is only approximately 1 kJ/mol. This discrepancy is related to a strong enthalpy-entropy compensation due, most likely, to the differences in hydration of the protonated and deprotonated forms of the alpha-amino group. (+info)
Approximate entropy as an electroencephalographic measure of anesthetic drug effect during desflurane anesthesia.
(24/1338)
BACKGROUND: The authors hypothesized that the electroencephalogram (EEG) during higher anesthetic concentrations would show more "order" and less "randomness" than at lower anesthetic concentrations. "Approximate entropy" is a new statistical parameter derived from the Kolmogorov-Sinai entropy formula which quantifies the amount of regularity in data. The approximate entropy quantifies the predictability of subsequent amplitude values of the EEG based on the knowledge of the previous amplitude values. The authors investigated the dose-response relation of the EEG approximate entropy during desflurane anesthesia in comparison with spectral edge frequency 95, median frequency, and bispectral index. METHODS: Twelve female patients were studied during gynecologic laparotomies. Between opening and closure of the peritoneum, end-tidal desflurane concentrations were varied between 0.5 and 1.6 minimum alveolar concentration (MAC). The EEG approximate entropy, median EEG frequency, spectral edge frequency 95, and bispectral index were determined and the performance of each to predict the desflurane effect compartment concentration, obtained by simultaneous pharmacokinetic-pharmacodynamic modeling, was compared. RESULTS: Electroencephalogram approximate entropy decreased continuously over the observed concentration range of desflurane. The performance of the approximate entropy (prediction probability PK = 0.86 +/- 0.06) as an indicator for desflurane concentrations is similar to spectral edge frequency 95 (PK = 0.86 +/- 0.06) and bispectral index (PK = 0.82 +/- 0.06) and is statistically significantly better than median frequency (PK = 0.78 +/- 0.06). CONCLUSIONS: The amount of regularity in the EEG increases with increasing desflurane concentrations. The approximate entropy could be a useful EEG measure of anesthetic drug effect. (+info)