Joseph P. Zbilut

Nonlinear Methods in the Analysis of Protein Sequences: A Case Study in Rubredoxins

Two computational methods widely used in time series analysis were applied to protein sequences, and their ability to derive structural information not directly accessible through classical sequence comparisons methods was assessed. The primary structures of 19 rubredoxins of both mesophilic and thermophilic bacteria, coded with hydrophobicity values of amino acid residues, were considered as time series and were analyzed by 1) recurrence quantification analysis and 2) spectral analysis of the sequence major eigenfunctions. The results of the two methods agreed to a large extent and generated a classification consistent with known 3D structural characteristics of the studied proteins. This classification separated in a clearcut manner a thermophilic protein from mesophilic proteins. The classification of primary structures given by the two dynamical methods was demonstrated to be basically different from classification stemming from classical sequence homology metrics. Moreover, on a more detailed scale, the method was able to discriminate between thermophilic and mesophilic proteins from a set of chimeric sequences generated from the mixing of a mesophilic (Rubr Clopa) and a thermophilic (Rubr Pyrfu) protein. Overall, our results point to a new way of looking at protein sequence comparisons.

On-line runaway detection in isoperibolic batch and semibatch reactors using the divergence criterion

We present a method for early detection of runaway initiation in batch and semibatch isoperibolic reactors using only temperature measurements, and based on the calculation of the divergence of the system by applying state space reconstruction techniques. The method is illustrated for simulated as well as experimental data sets. The results show that the algorithm is able to distinguish between runaway and non-runaway situations and it does not produce false alarms even during semibatch dosed-controlled experiments. For the case of the experimental data sets, due to fluctuations and noise present in the measurements, it is necessary to apply non-linear filters to improve the performance in terms of early detection and number of false alarms. Finally, we show that the divergence is a generalisation of former criteria for on-line detection.

Dimensional analysis of heart rate variability in heart transplant recipients

Abstract Periodicities in the heart rate have been known for some time. We discuss these periodicities in normal and transplanted hearts. We then consider the possibility of dimensional analysis of these periodicities in transplanted hearts and problems associated with the record.

Treatment of sepsis and septic shock: a review.

Septic shock is one of the leading causes of death in intensive care units, and its incidence is increasing. Mortality rates as high as 95% are reported, with rates of 60% or more even when diagnosed and treated promptly. This review examines the definition of septic shock, its pathogenesis, and supportive therapy, with particular attention to intervention during the septic shock cascade.

A Markovian formalization of heart rate dynamics evinces a quantum-like hypothesis

Most investigations into heart rate dynamics have emphasized continuous functions, whereas the heart beat itself is a discrete event. We present experimental evidence that by considering this quality, the dynamics may be appreciated as a result of singular dynamics arising out of non-Lipschitz formalisms. Markov process analysis demonstrates that heart beats may then be considered in terms of quantum-like constraints.

Discrimination of single amino acid mutations of the p53 protein by means of deterministic singularities of recurrence quantification analysis

p53 is mutated in roughly 50% of all human tumors, predominantly in the DNA‐binding domain codons. Structural, biochemical, and functional studies have reported that the different p53 mutants possess a broad range of behaviors that include the elimination of the tumor‐suppression function of wild‐type protein, the acquisition of dominant‐negative function over the wild‐type form, and the establishment of gain‐of‐function activities. The contribution of each of these types of mutations to tumor progression, grade of malignancy, and response to anticancer treatments has been so far analyzed only for a few “hot‐spots.” In an attempt to identify new approaches to systematically characterize the complete spectrum of p53 mutations, we applied recurrence quantification analysis (RQA), a non‐linear signal analysis technique, to p53 primary structure. Moving from the study of the p53 hydrophobicity pattern, which revealed important similarities with the singular deterministic structuring of prions, we could statistically discriminate, on a pure amino acid sequence basis, between experimentally characterized DNA‐contact defective and conformational p53 mutants with a very high percentage of success. This result indicates that RQA is a mathematical tool particularly advantageous for the development of a database of p53 mutations that integrates epidemiological data with structural and functional categorizations. Proteins 2004;55:000–000.

Singularities of the heart beat as demonstrated by recurrence quantification analysis

Deterministic, chaotic, nonlinear dynamics have enjoyed considerable popularity in the analysis of physiological systems. Many models, however, fail to incorporate some basic features of the involved physiology. The authors research using experimental data from ECGs analyzed by recurrence quantification analysis (RQA) suggest that some of these dynamics can be better modeled by singularities of differential equations, alternating with oscillations which result in multi-choice responses to excitations. ECGs of 34 healthy volunteers were recorded for 512 consecutive beats. Recurrence plots suggested discontinuities at the T-P interval, and the durations of the T-P and P-T intervals were manually calculated. Although the distributions of these two intervals were found to be similar (KS two sample test, p=NS), RQA demonstrated that the T-P Interval approached the embedding limit of pseudo random numbers [pseudo random=4; T-P=4; (95% CI=3.64.3)]. This suggests the primary stochastic process of ECGs is located In the T-P interval and represents a singularity of the dynamics alternating with the determinism of the P-T interval. The dynamics are thus discontinuous and poorly represented by FFT and other, nonlinear transform techniques.

Use of a power law scaling relationship to analyze signal averaged ECGs

Signal-averaged electrocardiograms (ECGs) have established themselves as a useful means for the detection of late potentials. Unfortunately debate continues as to the best strategies for their analysis. A method which treats late potentials as part of the inherent noise of the signal is that of power law scaling. It was used retrospectively to analyze signal-averaged ECGs. Significant differences in the scaling exponents for patients with myocardial infarction, regional wall motion abnormality, and dilated cardiomyopathy were demonstrated. These preliminary findings suggest that the entire frequency range of the signal-averaged ECG may contain important clinically useful data.<<ETX>>