Assessment of Dispersion and Bubble Entropy Measures for Enhancing Preterm Birth Prediction Based on Electrohysterographic Signals

[EN] One of the remaining challenges for the scientific-technical community is predicting preterm births, for which electrohysterography (EHG) has emerged as a highly sensitive prediction technique. Sample and fuzzy entropy have been used to characterize EHG signals, although they require optimizing many internal parameters. Both bubble entropy, which only requires one internal parameter, and dispersion entropy, which can detect any changes in frequency and amplitude, have been proposed to characterize biomedical signals. In this work, we attempted to determine the clinical value of these entropy measures for predicting preterm birth by analyzing their discriminatory capacity as an individual feature and their complementarity to other EHG characteristics by developing six prediction models using obstetrical data, linear and non-linear EHG features, and linear discriminant analysis using a genetic algorithm to select the features. Both dispersion and bubble entropy better discriminated between the preterm and term groups than sample, spectral, and fuzzy entropy. Entropy metrics provided complementary information to linear features, and indeed, the improvement in model performance by including other non-linear features was negligible. The best model performance obtained an F1-score of 90.1 ± 2% for testing the dataset. This model can easily be adapted to real-time applications, thereby contributing to the transferability of the EHG technique to clinical practice.This work was supported by the Spanish Ministry of Economy and Competitiveness, the European Regional Development Fund (MCIU/AEI/FEDER, UE RTI2018-094449-A-I00-AR), and by the Generalitat Valenciana (AICO/2019/220)Nieto Del-Amor, F.; Beskhani, R.; Ye Lin, Y.; Garcia-Casado, J.; Díaz-Martínez, MDA.; Monfort-Ortiz, R.; Diago-Almela, VJ.... (2021). Assessment of Dispersion and Bubble Entropy Measures for Enhancing Preterm Birth Prediction Based on Electrohysterographic Signals. Sensors. 21(18):1-17. https://doi.org/10.3390/s21186071S117211

Local Cooperativity Mechanism in the DNA Melting Transition

We propose a new statistical mechanics model for the melting transition of DNA. Base pairing and stacking are treated as separate degrees of freedom, and the interplay between pairing and stacking is described by a set of local rules which mimic the geometrical constraints in the real molecule. This microscopic mechanism intrinsically accounts for the cooperativity related to the free energy penalty of bubble nucleation. The model describes both the unpairing and unstacking parts of the spectroscopically determined experimental melting curves. Furthermore, the model explains the observed temperature dependence of the effective thermodynamic parameters used in models of the nearest neighbor (NN) type. We compute the partition function for the model through the transfer matrix formalism, which we also generalize to include non local chain entropy terms. This part introduces a new parametrization of the Yeramian-like transfer matrix approach to the Poland-Scheraga description of DNA melting. The model is exactly solvable in the homogeneous thermodynamic limit, and we calculate all observables without use of the grand partition function. As is well known, models of this class have a first order or continuous phase transition at the temperature of complete strand separation depending on the value of the exponent of the bubble entropy.Comment: Extended version of Phys. Rev. E pape

Permutation Entropy and Bubble Entropy: Possible interactions and synergies between order and sorting relations

[EN] Despite its widely demonstrated usefulness, there is still room for improvement in the basic Permutation Entropy (PE) algorithm, as several subsequent studies have proposed in the recent years. For example, some improved PE variants try to address possible PE weaknesses, such as its only focus on ordinal information, and not on amplitude, or the possible detrimental impact of equal values in subsequences due to motif ambiguity. Other evolved PE methods try to reduce the influence of input parameters. A good representative of this last point is the Bubble Entropy (BE) method. BE is based on sorting relations instead of ordinal patterns, and its promising capabilities have not been extensively assessed yet. The objective of the present study was to comparatively assess the classification performance of this new method, and study and exploit the possible synergies between PE and BE. The claimed superior performance of BE over PE was first evaluated by conducting a series of time series classification tests over a varied and diverse experimental set. The results of this assessment apparently suggested that there is a complementary relationship between PE and BE, instead of a superior/inferior relationship. A second set of experiments using PE and BE simultaneously as the input features of a clustering algorithm, demonstrated that with a proper algorithm configuration, classification accuracy and robustness can benefit from both measures.Cuesta Frau, D.; Vargas-Rojo, B. (2020). Permutation Entropy and Bubble Entropy: Possible interactions and synergies between order and sorting relations. Mathematical Biosciences and Engineering. 17(2):1637-1658. https://doi.org/10.3934/mbe.2020086S163716581721. C. Bandt and B. Pompe, Permutation entropy: A natural complexity measure for time series, Phys. Rev. Lett., 88 (2002), 174102.2. M. Zanin, L. Zunino, O. A. Rosso and D. 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Entanglement entropy of a quantum unbinding transition and entropy of DNA

Two significant consequences of quantum fluctuations are entanglement and criticality. Entangled states may not be critical but a critical state shows signatures of universality in entanglement. A surprising result found here is that the entanglement entropy may become arbitrarily large and negative near the dissociation of a bound pair of quantum particles. Although apparently counter-intuitive, it is shown to be consistent and essential for the phase transition, by mapping to a classical problem of DNA melting. We associate the entanglement entropy to a subextensive part of the entropy of DNA bubbles, which is responsible for melting. The absence of any extensivity requirement in time makes this negative entropy an inevitable consequence of quantum mechanics in continuum. Our results encompass quantum critical points and first-order transitions in general dimensions.Comment: v2: 6 pages, 3 figures (title modified, more details and figures added

Melting behavior and different bound states in three-stranded DNA models

Thermal denaturation of DNA is often studied with coarse-grained models in which native sequential base pairing is mimicked by the existence of attractive interactions only between monomers at the same position along strands (Poland and Scheraga models). Within this framework, the existence of a three strand DNA bound state in conditions where a duplex DNA would be in the denaturated state was recently predicted from a study of three directed polymer models on simplified hierarchical lattices ($d>2$) and in $1+1$ dimensions. Such phenomenon which is similar to the Efimov effect in nuclear physics was named Efimov-DNA. In this paper we study the melting of the three-stranded DNA on a Sierpinski gasket of dimensions $d<2$ by assigning extra weight factors to fork openings and closings, to induce a two-strand DNA melting. In such a context we can find again the existence of the Efimov-DNA-like state but quite surprisingly we discover also the presence of a different phase, to be called a mixed state, where the strands are pair-wise bound but without three chain contacts. Whereas the Efimov DNA turns out to be a crossover near melting, the mixed phase is a thermodynamic phase.Comment: corrected file uploade

On the standardization of approximate entropy: multidimensional approximate entropy index evaluated on short-term HRV time series

Background. Nonlinear heart rate variability (HRV) indices have extended the description of autonomic nervous system (ANS) regulation of the heart. One of those indices is approximate entropy, ApEn, which has become a commonly used measure of the irregularity of a time series. To calculate ApEn, a priori definition of parameters like the threshold on similarity and the embedding dimension is required, which has been shown to be critical for interpretation of the results. Thus, searching for a parameter-free ApEn-based index could be advantageous for standardizing the use and interpretation of this widely applied entropy measurement. Methods. A novel entropy index called multidimensional approximate entropy, , is proposed based on summing the contribution of maximum approximate entropies over a wide range of embedding dimensions while selecting the similarity threshold leading to maximum ApEn value in each dimension. Synthetic RR interval time series with varying levels of stochasticity, generated by both MIX(P) processes and white/pink noise, were used to validate the properties of the proposed index. Aging and congestive heart failure (CHF) were characterized from RR interval time series of available databases. Results. In synthetic time series, values were proportional to the level of randomness; i.e., increased for higher values of P in generated MIX(P) processes and was larger for white than for pink noise. This result was a consequence of all maximum approximate entropy values being increased for higher levels of randomness in all considered embedding dimensions. This is in contrast to the results obtained for approximate entropies computed with a fixed similarity threshold, which presented inconsistent results for different embedding dimensions. Evaluation of the proposed index on available databases revealed that aging was associated with a notable reduction in values. On the other hand, evaluated during the night period was considerably larger in CHF patients than in healthy subjects. Conclusion. A novel parameter-free multidimensional approximate entropy index, , is proposed and tested over synthetic data to confirm its capacity to represent a range of randomness levels in HRV time series. values are reduced in elderly patients, which may correspond to the reported loss of ANS adaptability in this population segment. Increased values measured in CHF patients versus healthy subjects during the night period point to greater irregularity of heart rate dynamics caused by the disease

Time-dependent Circulation Flows: Iron Enrichment in Cooling Flows with Heated Return Flows

We describe a new type of dynamical model for hot gas in galaxy groups and clusters in which gas moves simultaneously in both radial directions. Circulation flows are consistent with (1) the failure to observe cooling gas in X-ray spectra, (2) multiphase gas observed near the centers of these flows and (3) the accumulation of iron in the hot gas from Type Ia supernovae in the central galaxy. Dense inflowing gas cools, producing a positive central temperature gradient, as in normal cooling flows. Bubbles of hot, buoyant gas flow outward. Circulation flows eventually cool catastrophically if the outward flowing gas transports mass but no heat; to maintain the circulation both mass and energy must be supplied to the inflowing gas over a large volume, extending to the cooling radius. The rapid radial recirculation of gas produces a flat central core in the gas iron abundance, similar to many observations. We believe the circulation flows described here are the first gasdynamic, long-term evolutionary models that are in good agreement with all essential features observed in the hot gas: little or no gas cools as required by XMM spectra, the gas temperature increases outward near the center, and the gaseous iron abundance is about solar near the center and decreases outward.Comment: 17 pages (emulateapj5) with 6 figures; accepted by The Astrophysical Journa