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At least 595 records · Page 33Linked to original sources
arXiv1999

Modelling a Parasystolic Rhythm in a Heart-Transplant Patient

A parasystole from a heart-transplant patient is analysed using a beat-to-beat RR interval time series obtained from an electrocardiogram (ECG). The dysrhythmia, resulting from the co-existence of two pacemakers, the sinus node and an ectopic focus, presents distinctive regular patterns, with transitions from one pattern to another occurring abruptly. It is shown that the parasystolic rhythm can be simulated by a model involving two oscillators firing at fixed rates, under the restriction that neither is allowed to fire during the other's refractory period. It is found that the structure of the generated RR time series is essentially determined by the ratio of the period of the two oscillators. In the case of a heart-transplant patient with a small heart-rate variability as a result of heart denervation, the model predicts the RR intervals with an error of less than 6% for an 80-beat sequence. From a physiological point of view, the results imply that the interaction between the two pacemakers in the heart is fairly weak, and hence the parasystole observed in the heart-transplant patient can be modelled as a pure parasystole.

physics.med-ph↗
arXiv1999

Genetic Algorithms in Time-Dependent Environments

The influence of time-dependent fitnesses on the infinite population dynamics of simple genetic algorithms (without crossover) is analyzed. Based on general arguments, a schematic phase diagram is constructed that allows one to characterize the asymptotic states in dependence on the mutation rate and the time scale of changes. Furthermore, the notion of regular changes is raised for which the population can be shown to converge towards a generalized quasispecies. Based on this, error thresholds and an optimal mutation rate are approximately calculated for a generational genetic algorithm with a moving needle-in-the-haystack landscape. The so found phase diagram is fully consistent with our general considerations.

physics.bio-ph↗
arXiv2005

Evaluation of the Extension of the Cerebral Blood Flow and its Main Parameters

Among the major factors controlling the cerebral blood flow (CBF) - cerebral perfusion pressure, arterial partial pressure of oxygen (PaO2), cerebral metabolism, arterial partial pressure of carbon dioxide (PaCO2), and cardiac output, the effect of PaCO2 is peculiar in being independent of autoregulatory CBF mechanisms and it allows to explore the full range of the CBF. We have developed a simple physical model, and have derived a simple four parameter formula, relating the CBF to PaCO2. The parameters can be extracted in an easy way, directly from the experimental data. With this model five experimental data sets of human, rats, baboons and dogs were well fitted. The same type of parametrization was also used successfully for fitting experimental data of PaO2 of dogs. We have also looked on the dependence of the parameters on other factors and were able to evaluate their dependence on the mean arterial blood pressure.

physics.med-ph↗
arXiv1999

Residue profile in predivergence sequences as a guide to the origin of DNA replication

DNA dependent RNA polymerase core subunits abb' conserved residues at frequencies most closely matched with codons at stage 10.4-11.1 in code evolution. An excess of acidic residues (stage 2 additions) lowered this estimate, but not by more than 2.3 stages. With 1 tryptophan (stage 14 addition) in 529 conserved residues, abb' significantly under-represented this amino acid, consistent with a cut-off in its residue profile before completion of the genetic code. Residue profiles in FEN-1 homologs and DNA topoisomerase I-5' placed their origin at stage 11-13. Prokaryote septation protein, FtsZ, arose earlier, between stage 8-11. Proteolipid in an ATP-driven proton pump served as a marker for cell membrane formation. It indicated this event took place near stage 7. Cell division, DNA replication and transcription were inferred to have originated in a protocell antecedent of the last common ancestor. Late-forming residue profiles characterized RNA dependent RNA replicase, DNA polymerase, reverse transcriptase and ribonucleotide reductase. This suggests some early processes, including RNA replication and deoxynucleotide synthesis, once depended on catalysts not found in extant residue sequences. Early formation of topoisomerase I, and enzymes that synthesize and trim RNA-DNA hybrids was viewed as evidence for a mixed duplex, with linear RNA and DNA strands, in the transition from an RNA to DNA genome.

physics.bio-ph↗
arXiv1999

Correlation Dimension Maps of EEG from Epileptic Absences

Purpose: The understanding of brain activity, and in particular events such as epileptic seizures, lies on the characterisation of the dynamics of the neural networks. The theory of non-linear dynamics provides signal analysis techniques which may give new information on the behaviour of such networks. Methods: We calculated correlation dimension maps for 19-channel EEG data from 3 patients with a total of 7 absence seizures. The signals were analysed before, during and after the seizures. Phase randomised surrogate data was used to test chaos. Results: In the seizures of two patients we could distinguish two dynamical regions on the cerebral cortex, one that seemed to exhibit chaos whereas the other seemed to exhibit noise. The pattern shown is essentially the same for seizures triggered by hyperventilation, but differ for seizures triggered by light flashes. The chaotic dynamics that one seems to observe is determined by a small number of variables and has low complexity. On the other hand, in the seizures of another patient no chaotic region was found. Before and during the seizures no chaos was found either, in all cases. Conclusions: The application of non-linear signal analysis revealed the existence of differences in the spatial dynamics associated to absence seizures. This may contribute to the understanding of those seizures and be of assistance in clinical diagnosis.

physics.med-ph↗
arXiv1999

On the Biological Advantage of Chirality

The presence of chirality in the main molecules of life may well be not just a structural artifact, but of pure biological advantage. The possibility of the existence of a phenomenon of a special mode of interaction, labeled as "chiral interaction" (CI), for which structural chirality is a necessary condition, is the main reason for such an advantage. In order to demonstrate such a possibility, macroscopic chiral devices are introduced and presented as analogies for such an interaction. For this purpose it is important to make a clear distinction between geometric and physical chiralities, where the latter are capable to perform chiral interactions with various media. Apart from chirality, a few other structural elements are required. In particular, the presence of an interface that separates between the chiral device and the medium with which it is interacting. The physical chirality is build into this very interface where chiral interaction is taking place. On a molecular level, soluble proteins in particular, the active medium is the presence of random ionic motion in the aqueous solvent. As a result of chiral interaction a certain perturbation, or current, is generated and flowing along the coils of $ α$-helix structure in one preferred direction out of two possible ones. A model for such a chiral interaction is presented and a few significant consequences are pointed out. In particular, it is important to emphasize the time-irreversible feature of chiral interaction, which leads to its non-ergodic nature that is to be considered a necessary condition for evolutionary processes in biomolecules. There exists an experimental result by Careri et al. who found a clear linkage between the free protonic motion in the hydration layer of protein s and their enzymatic activity.

physics.bio-ph↗
arXiv2000

A Model of Convergent Extension in Animal Morphogenesis

In this paper we argue that the pattern of cell movements in the morphogenetic process known as convergent extension can be understood as a energy minimization process, provided the cell-cell adhesive energy has a certain kind of anisotropy. This single simple property is sufficient cause for the type of cell elongation, alignment, and intercalation of a cellular array that is the characteristic of convergent extension. We describe the type of anisotropy required. We show that the final aspect ratio of the array of cells is independent of the initial configuration and of the degree of cell elongation. We find how it depends on the anisotropy.

physics.bio-ph↗
arXiv2004

Semiclassical Neural Network

We have constructed a simple semiclassical model of neural network where neurons have quantum links with one another in a chosen way and affect one another in a fashion analogous to action potentials. We have examined the role of stochasticity introduced by the quantum potential and compare the system with the classical system of an integrate-and-fire model by Hopfield. Average periodicity and short term retentivity of input memory are noted.

quant-ph↗
arXiv2004

Neural Networks with c-NOT Gated Nodes

We try to design a quantum neural network with qubits instead of classical neurons with deterministic states, and also with quantum operators replacing teh classical action potentials. With our choice of gates interconnecting teh neural lattice, it appears that the state of the system behaves in ways reflecting both the strengths of coupling between neurons as well as initial conditions. We find that depending whether there is a threshold for emission from excited to ground state, the system shows either aperiodic oscillations or coherent ones with periodicity depending on the strength of coupling.

quant-ph↗
arXiv1998

DNA Transcription Mechanism with a Moving Enzyme

Previous numerical investigations of an one-dimensional DNA model with an extended modified coupling constant by transcripting enzyme are integrated to longer time and demonstrated explicitly the trapping of breathers by DNA chains with realistic parameters obtained from experiments. Furthermore, collective coordinate method is used to explain a previously observed numerical evidence that breathers placed far from defects are difficult to trap, and the motional effect of RNA-polymerase is investigated.

solv-int↗
arXiv1998

Selection, Mutations and Codon Usage in Bacterial Model

We present a statistical model of bacterial evolution based on the coupling between codon usage and tRNA abundance. Such a model interprets this aspect of the evolutionary process as a balance between the codon homogenization effect due to mutation process and the improvement of the translation phase due to natural selection. We develop a thermodynamical description of the asymptotic state of the model. The analysis of naturally occurring sequences shows that the effect of natural selection on codon bias not only affects genes whose products are largely required at maximal growth rate conditions but also gene products that undergo rapid transient increases.

cond-mat.stat-mech↗
arXiv1996

Mass Extinctions vs. Uniformitarianism in Biological Evolution

It is usually believed that Darwin's theory leads to a smooth gradual evolution, so that mass extinctions must be caused by external shocks. However, it has recently been argued that mass extinctions arise from the intrinsic dynamics of Darwinian evolution. Species become extinct when swept by intermittent avalanches propagating through the global ecology. These ideas are made concrete through studies of simple mathematical models of coevolving species. The models exhibit self-organized criticality and describe some general features of the extinction pattern in the fossil record.

cond-mat↗
arXiv1997

Modeling diffusion of innovations with probabilistic cellular automata

We present a family of one-dimensional cellular automata modeling the diffusion of an innovation in a population. Starting from simple deterministic rules, we construct models parameterized by the interaction range and exhibiting a second-order phase transition. We show that the number of individuals who eventually keep adopting the innovation strongly depends on connectivity between individuals.

adap-org↗
arXiv1996

Evolution on a smooth landscape

We study in detail a recently proposed simple discrete model for evolution on smooth landscapes. An asymptotic solution of this model for long times is constructed. We find that the dynamics of the population are governed by correlation functions that although being formally down by powers of $N$ (the population size) nonetheless control the evolution process after a very short transient. The long-time behavior can be found analytically since only one of these higher-order correlators (the two-point function) is relevant. We compare and contrast the exact findings derived herein with a previously proposed phenomenological treatment employing mean field theory supplemented with a cutoff at small population density. Finally, we relate our results to the recently studied case of mutation on a totally flat landscape.

cond-mat↗