Impact of artifact correction methods on R-R interbeat signals to quantifying heart rate variability (HRV) according to linear and nonlinear methods.

In the analysis of heart rate variability (HRV) are used temporal series that contains the distances between successive heartbeats in order to assess autonomic regulation of the cardiovascular system. These series are obtained from the electrocardiogram (ECG) signal analysis, which can be affected by different types of artifacts leading to incorrect interpretations in the analysis of the HRV signals. Classic approach to deal with these artifacts implies the use of correction methods, some of them based on interpolation, substitution or statistical techniques. However, there are few studies that shows the accuracy and performance of these correction methods on real HRV signals. This study aims to determine the performance of some linear and non-linear correction methods on HRV signals with induced artefacts by quantification of its linear and nonlinear HRV parameters. As part of the methodology, ECG signals of rats measured using the technique of telemetry were used to generate real heart rate variability signals without any error. In these series were simulated missing points (beats) in different quantities in order to emulate a real experimental situation as accurately as possible. In order to compare recovering efficiency, deletion (DEL), linear interpolation (LI), cubic spline interpolation (CI), moving average window (MAW) and nonlinear predictive interpolation (NPI) were used as correction methods for the series with induced artifacts. The accuracy of each correction method was known through the results obtained after the measurement of the mean value of the series (AVNN), standard deviation (SDNN), root mean square error of the differences between successive heartbeats (RMSSD), Lomb\'s periodogram (LSP), Detrended Fluctuation Analysis (DFA), multiscale entropy (MSE) and symbolic dynamics (SD) on each HRV signal with and without artifacts. The results show that, at low levels of missing points the performance of all correction techniques are very similar with very close values for each HRV parameter. However, at higher levels of losses only the NPI method allows to obtain HRV parameters with low error values and low quantity of significant differences in comparison to the values calculated for the same signals without the presence of missing points.

Primary and secondary metabolites production in signal grass around the year under nitrogen fertilizer

Plants produce a number of substances and products and primary and secondary metabolites (SM) are amongst them with many benefits but limitation as well. Usually, the fodder are not considered toxic to animals or as a source having higher SM. The Brachiaria decumbens has a considerable nutritional value, but it is considered as a toxic grass for causing photosensitization in animals, if the grass is not harvested for more than 30 days or solely. The absence of detailed information in the literature about SM in Brachiaria, metabolites production and its chemical profile enable us to focus not only on the nutritive value but to get answers in all aspects and especially on toxicity. The study was conducted in the period of december 2013 to december 2014; in greenhouse FZEA-USP. B. decumbens was used with two cutting heights (10 and 20 cm) and nitrogen doses (0, 150, 300 and 450 kg ha-1) in complete randomized block design. The bromatological analysis were carried out on near infrared spectroscopy. Generally, the application of 150 kg ha-1 N was sufficient to promote the nutritional value in B. decumbens but above it the nitrogen use efficiency decline significantly. The highest dry matter yield (99.97 g/pot) was observed in autumn and the lowest was in winter (30.20 g/pot). While, as per nitrogen dose the average highest dry matter yield was at 150 kg ha-1 (79.98 g/pot). The highest crude protein was observed in winter (11.88%) and the lowest in autumn (7.78%). By the cutting heights; the 10 cm proved to have high CP (9.51%). In respect of fibrous contents, the highest acid detergent fiber was noted in summer (36.37%) and lowest in winter (30.88%). While the neutral detergent fiber was being highest in autumn and lowest in spring (79.60%). The highest in vitro dry matter and organic matter digestibilities were noted at 300 kg ha-1 N; being 68.06 and 60.57%; respectively; with the lowest observed in without N treatments (62.63% and 57.97), respectively. For determination of the classes, types and concentration of SM in B. decumbens, phytochemical tests, thin layer and liquid chromatography-mass spectrometry and nuclear magnetic resonance analysis were carried out. Height, nitrogen and seasons significantly (P <0.0001) affected the secondary metabolic profile. A new protodioscin isomer (protoneodioscin (25S-)) was identified for first time in B. decumbens and is supposed to be the probable toxicity reason. Its structure was verified by 1D and 2D NMR techniques (1H, 13C) and 1D (COSY-45, edited HSQC, HMBC, H2BC, HSQC -TOCSY, NOESY and 1 H, 1 H, J). All factors influence the metabolic profile significantly (P <0.0001). The lowest phenols were at 300 kg ha-1 while the lowest flavones were at 0 kg ha-1. Season wise the highest phenols occurred in autumn (19.65 mg/g d.wt.) and highest flavones (28.87 mg/g d.wt.) in spring. Seasons effect the saponin production significantly (P <0.0001) and the results showed significant differences in the protodioscin (17.63±4.3 - 22.57±2.2 mg/g d.wt.) and protoneodioscin (23.3±1.2 - 31.07±2.9 mg/g d.wt.) concentrations. The highest protodioscin isomers concentrations were observed in winter and spring and by N doses the highest were noted in 300 kg ha-1. Simply, all factors significantly played their role in varying concentrations of secondary metabolites.