Comparative effect of bisoprolol and losartan in the treatment of essential hypertension

Objective: We investigated the effects of bisoprolol and losartan on subjects with essential hypertension, by conducting heart rate variability (HRV) analysis of ECG signals. Our intention was to establish the set of linear and nonlinear heart rate variability parameters, which could be used as a noninvasive markers in the treatment of hypertension. Materials and Methods: Sixty subjects with essential hypertension included in this study were divided in two groups. During the four weeks medical treatment, the first group was administered with daily oral dose of 5 mg of bisoprolol and the second with daily oral dose of 50 mg of losartan. We recorded ECG signals, and performed HRV analysis of consecutive RR time intervals, before and after a month of pharmacological therapy. Results: In the case of bisoprolol, statistically the most significant changes of HRV parameters were: TP (1814.1 +/- 1731.3 ms(2) vs. 761.3 +/- 725.0 ms(2), P LT 0.0001), RR (870.2 +/- 105.7 ms vs. 1027.2 +/- 150.0 ms, P LT 0.0001), HR (70.81 +/- 8.42 bp/min vs. 60.10 +/- 9.52 bp/min, P LT 0.0001). In the case of losartan, the most significant changes were: SDNN (43.16 +/- 17.27 ms vs. 237.98 +/- 118.54 ms, P = 0.002), rmSDD (27.09 +/- 18.27 ms vs. 46.82 +/- 37.71 ms, P = 0.003), SD2 (55.18 +/- 20.6 vs. 70.67 +/- 26.12, P LT 0.019) and DF2 (0.69 +/- 0.21 vs. 0.86 +/- 0.25, P LT 0.014). Conclusion: Effects of bisoprolol and losartan were especially manifested among the set of linear HRV parameters. As a consequence of effect of losartan, we singled out the nonlinear parameters SD2 and DF2

Comparative effect of bisoprolol and losartan in the treatment of essential hypertension

Objective: We investigated the effects of bisoprolol and losartan on subjects with essential hypertension, by conducting heart rate variability (HRV) analysis of ECG signals. Our intention was to establish the set of linear and nonlinear heart rate variability parameters, which could be used as a noninvasive markers in the treatment of hypertension. Materials and Methods: Sixty subjects with essential hypertension included in this study were divided in two groups. During the four weeks medical treatment, the first group was administered with daily oral dose of 5 mg of bisoprolol and the second with daily oral dose of 50 mg of losartan. We recorded ECG signals, and performed HRV analysis of consecutive RR time intervals, before and after a month of pharmacological therapy. Results: In the case of bisoprolol, statistically the most significant changes of HRV parameters were: TP (1814.1 +/- 1731.3 ms(2) vs. 761.3 +/- 725.0 ms(2), P LT 0.0001), RR (870.2 +/- 105.7 ms vs. 1027.2 +/- 150.0 ms, P LT 0.0001), HR (70.81 +/- 8.42 bp/min vs. 60.10 +/- 9.52 bp/min, P LT 0.0001). In the case of losartan, the most significant changes were: SDNN (43.16 +/- 17.27 ms vs. 237.98 +/- 118.54 ms, P = 0.002), rmSDD (27.09 +/- 18.27 ms vs. 46.82 +/- 37.71 ms, P = 0.003), SD2 (55.18 +/- 20.6 vs. 70.67 +/- 26.12, P LT 0.019) and DF2 (0.69 +/- 0.21 vs. 0.86 +/- 0.25, P LT 0.014). Conclusion: Effects of bisoprolol and losartan were especially manifested among the set of linear HRV parameters. As a consequence of effect of losartan, we singled out the nonlinear parameters SD2 and DF2

Spectral and fractal analysis of cerebellar activity after single and repeated brain injury

The cerebellum, even when not directly damaged, is potentially interesting for understanding the adaptive responses to brain injury. Cerebellar electrocortical activity (ECoG) in rats was studied using spectral and fractal analysis after single and repeated unilateral injury of the parietal cortex. Local field potentials of cerebellar paravermal cortex were recorded before brain injury, in the acute phase (up to 2.5 hours) after a first injury of anesthetized rats, and then before and after second, third, and, in some cases, fourth injury. Relative gamma power (32.1-128.0 Hz) and fractal dimension of ECoGs were temporarily increased after the first injury. However, there was a permanent mild increase in gamma activity and a mild increase in the fractal dimension of cerebellar activity as a chronic change after repeated remote brain injury. There was a negative linear correlation between the normalized difference in fractal dimensions and normalized difference in gamma powers of cerebellar activity only in the case of repeated brain injury. This is the first study showing that correlation between the parameters of spectral and fractal analyses of cerebellar activity can discriminate between single and repeated brain injuries, and is, therefore, a promising approach for identifying specific pathophysiological states

Signatures of Depression in Non-Stationary Biometric Time Series

This paper is based on a discussion that was held during a special session on models of mental disorders, at the NeuroMath meeting in Stockholm, Sweden, in September 2008. At this occasion, scientists from different countries and different fields of research presented their research and discussed open questions with regard to analyses and models of mental disorders, in particular depression. The content of this paper emerged from these discussions and in the presentation we briefly link biomarkers (hormones), bio-signals (EEG) and biomaps (brain-maps via EEG) to depression and its treatments, via linear statistical models as well as nonlinear dynamic models. Some examples involving EEG-data are presented