J.M. Nieto-Villar

Artificial neural network for normal, hypertensive, and preeclamptic pregnancy classification using maternal heart rate variability indexes

Objective. A model construction for classification of women with normal, hypertensive and preeclamptic pregnancy in different gestational ages using maternal heart rate variability (HRV) indexes. Method and patients. In the present work, we applied the artificial neural network for the classification problem, using the signal composed by the time intervals between consecutive RR peaks (RR) (n = 568) obtained from ECG records. Beside the HRV indexes, we also considered other factors like maternal history and blood pressure measurements. Results and conclusions. The obtained result reveals sensitivity for preeclampsia around 80% that increases for hypertensive and normal pregnancy groups. On the other hand, specificity is around 85–90%. These results indicate that the combination of HRV indexes with artificial neural networks (ANN) could be helpful for pregnancy study and characterization.

Blood Pressure and Heart Rate Variability Complexity Analysis in Pregnant Women with Hypertension

Background. In this work, we perform a comparative analysis of blood pressure and heart rate variability complexity during pregnancy between normal, hypertensive, and preeclamptic women. Methods and Results. A total of 563 short electrocardiographic (10 min) records were obtained from 217 pregnant women (135 normal, 55 hypertensive, and 27 preeclamptic) during several gestational ages in sitting position. We used a mixed unbalanced model for the longitudinal statistical analysis and besides the conventional spectral analysis, we applied Lempel–Ziv complexity, sample entropy, approximated entropy, and detrended fluctuation analysis in the complexity measurement. Conclusions. The obtained results revealed significant differences between pathological and normal states with important considerations related to pregnancy adaptability and evolution as well as the relationship of complexity and blood pressure with factors such as maternal age, familial history of diabetes or hypertension, and parity.

Heart rate variability complexity in the aging process

In the present work, we propose a discrete model to the characterization of heart rate variability (HRV) complexity in the aging process of healthy subjects. We apply the Shannon entropy on the basis of an alternative way to probability calculation and to define a new index taking into consideration the transition probability that is related to the physiological complexity of the system. Our results suggest that in the aging process the capability response decreases according to the reduction of the physiological complexity. In the oldest group, an alternative mechanism emerges to compensate for this lack of capability; however, this effect does not increase the physiological complexity. Concomitantly, we provide some physiological explanation for our results.

Relationship between Heart Rate Variability Indexes and Common Biochemical Markers in Normal and Hypertensive Third Trimester Pregnancy

Background. In this study, we explored the correlations between heart rate variability indexes and some biochemical markers during the third trimester of normal, hypertensive, and preeclamptic pregnancies. Methods and Results. The obtained indexes are associated with complexity and spectral variables calculated from short electrocardiographic records. Conclusions. Including all the subjects in the analysis, we found that complexity indexes are positively related with hemoglobin concentration in the pathologic group and uric acid blood levels whereas low frequency (LF) was negatively correlated with uric acid and creatinine concentration as well as positively correlated with platelet levels. The LF was the only spectral region with significant correlation. Through an independent analysis of groups, only significant correlations were found in normal and preeclamptic groups between LF and uric acid concentration and in normal and hypertensive groups for LF and creatinine blood levels.

The Rössler system as a model for chronotherapy

The biological systems are opened and are kept far from thermodynamics equilibrium. For these reasons, biological systems are always exposed to external perturbations, which may produce alterations on these rhythms as a consequence of coupling synchronization of the autonomous oscillator with perturbation. Coupling of therapeutic perturbations, such as drugs and radiation, on biological systems delivery to biological rhythms is known as chronotherapy. We used the Rossler system as a theoretical model for chronotherapy, generalized this formalism for chaotic behaviour. We found that when the Rossler is more dissipative, such as c increase, the systems become more robust to the perturbations.

Theoretical models for chronotherapy: periodic perturbations in hyperchaos.

In this work, a hyperchaotic system was used as a model for chronotherapy. We applied a periodic perturbation to a variable, varying the period and amplitude of forcing. The system, five-dimensional, has until three positive Lyapunov exponents. As a result, we get small periodical windows, but it was possible to get large areas of hyperchaos of two positive Lyapunov exponents from a chaotic behavior. In this chronotherapy model, chaos could be considered as a dynamical disease, and therapy goal must be to restore the hyperchaotic state.

Theoretical models in chronotherapy: II. Periodic perturbations in a chaotic chemical reaction

Abstract In this work, the Rössler system is used as a model for chronotherapy. We applied a periodic perturbation to the y variable to take the Rössler system from a chaotic behaviour to a simple periodic one, varying the period and amplitude of forcing. Some periodical windows and period-doubling cascades are observed. The most important of them is the large period-1 area around T 0 = 6.154 (the period corresponding to the dominant frequency in the power spectrum). This is a wide region as is desired in a chronotherapy model, where the therapy is administered, with ample tolerance, to transform a chaotic behaviour into a periodic one.

Protein surface roughness accounts for binding free energy of Plasmepsin II-ligand complexes

The calculation of absolute binding affinities for protein‐inhibitor complexes remains as one of the main challenges in computational structure‐based ligand design. The present work explored the calculations of surface fractal dimension (as a measure of surface roughness) and the relationship with experimental binding free energies of Plasmepsin II complexes. Plasmepsin II is an attractive target for novel therapeutic compounds to treat malaria. However, the structural flexibility of this enzyme is a drawback when searching for specific inhibitors. Concerning that, we performed separate explicitly solvated molecular dynamics simulations using the available high‐resolution crystal structures of different Plasmepsin II complexes. Molecular dynamics simulations allowed a better approximation to systems dynamics and, therefore, a more reliable estimation of surface roughness. This constitutes a novel approximation in order to obtain more realistic values of fractal dimension, because previous works considered only x‐ray structures. Binding site fractal dimension was calculated considering the ensemble of structures generated at different simulation times. A linear relationship between binding site fractal dimension and experimental binding free energies of the complexes was observed within 20 ns. Previous studies of the subject did not uncover this relationship. Regression model, coined FD model, was built to estimate binding free energies from binding site fractal dimension values. Leave‐one‐out cross‐validation showed that our model reproduced accurately the absolute binding free energies for our training set (R2 = 0.76; <|error|> =0.55 kcal/mol; SDerror = 0.19 kcal/mol). The fact that such a simple model may be applied raises some questions that are addressed in the article.

Chronotherapy of cancer: periodic perturbations in vascular growth and metastasis

Abstract A non-autonomous model was developed for vascular tumor growth and cancer metastasis under periodic perturbations that simulate chronotherapy. It was found that for a critical amplitude and a perturbation frequency of twice the autonomous frequency in vascular growth, less complex and therefore less robust states are reached and the tumor population decreases. In metastasis, similar results were found for a perturbation frequency equal to the autonomous frequency. In metastasis, similar behaviors occur, for a perturbation’s frequency equal to the fundamental frequency of system.

Dose and frequency in cancer therapy. Theoretical non-autonomous model of p53 network

Abstract A non-autonomous model for the regulation of apoptosis by p53 is proposed as a model for cancer chronotherapy. A perturbation is introduced that simulates damage caused to DNA in a periodic regime. To characterize the resulting system dynamics, the techniques used were stroboscopic analysis, Poincare section and power spectrum. The complexity of the time series was determined using the LZ index. Periodic and quasi-periodic dynamics were obtained as the control parameters were varied. The less complex states are those corresponding to higher values of the amplitude which indicates a strict control of the dose is required on periodic treatments.