Time course of changes in heart rate and blood pressure variability in streptozotocin-induced diabetic rats treated with insulin

Autonomic neuropathy is a frequent complication of diabetes associated with higher morbidity and mortality in symptomatic patients, possibly because it affects autonomic regulation of the sinus node, reducing heart rate (HR) variability which predisposes to fatal arrhythmias. We evaluated the time course of arterial pressure and HR and indirectly of autonomic function (by evaluation of mean arterial pressure (MAP) variability) in rats (164.5 ± 1.7 g) 7, 14, 30 and 120 days after streptozotocin (STZ) injection, treated with insulin, using measurements of arterial pressure, HR and MAP variability. HR variability was evaluated by the standard deviation of RR intervals (SDNN) and root mean square of successive difference of RR intervals (RMSSD). MAP variability was evaluated by the standard deviation of the mean of MAP and by 4 indices (P1, P2, P3 and MN) derived from the three-dimensional return map constructed by plotting MAPn x [(MAPn+1) - (MAPn)] x density. The indices represent the maximum concentration of points (P1), the longitudinal axis (P2), and the transversal axis (P3) and MN represents P1 x P2 x P3 x 10-3. STZ induced increased urinary glucose in diabetic (D) rats compared to controls (C). Seven days after STZ, diabetes reduced resting HR from 380.6 ± 12.9 to 319.2 ± 19.8 bpm, increased HR variability, as demonstrated by increased SDNN, from 11.77 ± 1.67 to 19.87 ± 2.60 ms, did not change MAP, and reduced P1 from 61.0 ± 5.3 to 51.5 ± 1.8 arbitrary units (AU), P2 from 41.3 ± 0.3 to 29.0 ± 1.8 AU, and MN from 171.1 ± 30.2 to 77.2 ± 9.6 AU of MAP. These indices, as well as HR and MAP, were similar for D and C animals 14, 30 and 120 days after STZ. Seven-day rats showed a negative correlation of urinary glucose with resting HR (r = -0.76, P = 0.03) as well as with the MN index (r = -0.83, P = 0.01). We conclude that rats with short-term diabetes mellitus induced by STZ presented modified autonomic control of HR and MAP which was reversible. The metabolic control may influence these results, suggesting that insulin treatment and a better metabolic control in this model may modify arterial pressure, HR and MAP variability

Methylmercury intoxication and histochemical demonstration of NADPH-diaphorase activity in the striate cortex of adult cats

The effects of methylmercury (MeHg) on histochemical demonstration of the NADPH-diaphorase (NADPH-d) activity in the striate cortex were studied in 4 adult cats. Two animals were used as control. The contaminated animals received 50 ml milk containing 0.42 µg MeHg and 100 g fish containing 0.03 µg MeHg daily for 2 months. The level of MeHg in area 17 of intoxicated animals was 3.2 µg/g wet weight brain tissue. Two cats were perfused 24 h after the last dose (group 1) and the other animals were perfused 6 months later (group 2). After microtomy, sections were processed for NADPHd histochemistry procedures using the malic enzyme method. Dendritic branch counts were performed from camera lucida drawings for control and intoxicated animals (N = 80). Average, standard deviation and Student t-test were calculated for each data group. The concentrations of mercury (Hg) in milk, fish and brain tissue were measured by acid digestion of samples, followed by reduction of total Hg in the digested sample to metallic Hg using stannous chloride followed by atomic fluorescence analysis. Only group 2 revealed a reduction of the neuropil enzyme activity and morphometric analysis showed a reduction in dendritic field area and in the number of distal dendrite branches of the NADPHd neurons in the white matter (P<0.05). These results suggest that NADPHd neurons in the white matter are more vulnerable to the long-term effects of MeHg than NADPHd neurons in the gray matter.

Together Everyone Achieves More? Herding Behavior in the Finnish Stock Market

This thesis examines whether or not Finnish stock markets has herding behavior. Sample data is from 2004 to 2013. Including total of 2516 market days. Market wide herding, up and down market herding, extreme price movement herding and turnover volume herding are measured in this thesis. Methods used in this thesis are cross-sectional absolute dispersion and cross-sectional standard deviation. This thesis found no signs of herding in the Finnish stock market.

Heart rate variability under resting conditions in postmenopausal and young women

The aim of the present study was to compare the modulation of heart rate in a group of postmenopausal women to that of a group of young women under resting conditions on the basis of R-R interval variability. Ten healthy postmenopausal women (mean ± SD, 58.3 ± 6.8 years) and 10 healthy young women (mean ± SD, 21.6 ± 0.82 years) were submitted to a control resting electrocardiogram (ECG) in the supine and sitting positions over a period of 6 min. The ECG was obtained from a one-channel heart monitor at the CM5 lead and processed and stored using an analog to digital converter connected to a microcomputer. R-R intervals were calculated on a beat-to-beat basis from the ECG recording in real time using a signal-processing software. Heart rate variability (HRV) was expressed as standard deviation (RMSM) and mean square root (RMSSD). In the supine position, the postmenopausal group showed significantly lower (P<0.05) median values of RMSM (34.9) and RMSSD (22.32) than the young group (RMSM: 62.11 and RMSSD: 49.1). The same occurred in the sitting position (RMSM: 33.0 and RMSSD: 18.9 compared to RMSM: 57.6 and RMSSD: 42.8 for the young group). These results indicate a decrease in parasympathetic modulation in postmenopausal women compared to young women which was possibly due both to the influence of age and hormonal factors. Thus, time domain HRV proved to be a noninvasive and sensitive method for the identification of changes in autonomic modulation of the sinus node in postmenopausal women.

Serial blood pressure measurements

The objective of the present investigation was to study the effects of a 60-s interval of venous congestion between two noninvasive measurements of arterial blood pressure (ABP) on the fluctuation of ABP, assessed by the standard deviation of the differences between two readings. ABP was measured in 345 successive patients, at rest, four times each. For 269 participants, one pair of readings was obtained with a 60-s interval and the other pair without an interval. For 76 patients, the first pair was read at the same interval, and the second pair had venous congestion interposed and there was no waiting interval. There was no increased ABP oscillation, either when there was no interval between ABP readings, or when venous congestion was interposed compared to pairs of ABP measurements performed with a 60-s interval. There was no increase in ABP oscillations when successive ABP readings were taken without an interval or even with venous congestion interposed. Contrary to the present belief, there seems to be no loss of reliability when blood pressure recordings are taken immediately one after another, in the clinical setting.

Effects of aerobic exercise training on heart rate variability during wakefulness and sleep and cardiorespiratory responses of young and middle-aged healthy men

The purpose of the present study was to evaluate the effects of aerobic physical training (APT) on heart rate variability (HRV) and cardiorespiratory responses at peak condition and ventilatory anaerobic threshold. Ten young (Y: median = 21 years) and seven middle-aged (MA = 53 years) healthy sedentary men were studied. Dynamic exercise tests were performed on a cycloergometer using a continuous ramp protocol (12 to 20 W/min) until exhaustion. A dynamic 24-h electrocardiogram was analyzed by time (TD) (standard deviation of mean R-R intervals) and frequency domain (FD) methods. The power spectral components were expressed as absolute (a) and normalized units (nu) at low (LF) and high (HF) frequencies and as the LF/HF ratio. Control (C) condition: HRV in TD (Y: 108, MA: 96 ms; P<0.05) and FD - LFa, HFa - was significantly higher in young (1030; 2589 ms²/Hz) than in middle-aged men (357; 342 ms²/Hz) only during sleep (P<0.05); post-training effects: resting bradycardia (P<0.05) in the awake condition in both groups; VO2 increased for both groups at anaerobic threshold (P<0.05), and at peak condition only in young men; HRV in TD and FD (a and nu) was not significantly changed by training in either groups. The vagal predominance during sleep is reduced with aging. The resting bradycardia induced by short-term APT in both age groups suggests that this adaptation is much more related to intrinsic alterations in sinus node than in efferent vagal-sympathetic modulation. Furthermore, the greater alterations in VO2 than in HRV may be related to short-term APT.

Simulating the dynamics of silver market using computational market dynamics

Traditional econometric approaches in modeling the dynamics of equity and commodity markets, have, made great progress in the past decades. However, they assume rationality among the economic agents and and do not capture the dynamics that produce extreme events (black swans), due to deviation from the rationality assumption. The purpose of this study is to simulate the dynamics of silver markets by using the novel computational market dynamics approach. To this end, the daily data from the period of 1st March 2000 to 1st March 2013 of closing prices of spot silver prices has been simulated with the Jabłonska-Capasso-Morale(JCM) model. The Maximum Likelihood approach has been employed to calibrate the acquired data with JCM. Statistical analysis of the simulated series with respect to the actual one has been conducted to evaluate model performance. The model captures the animal spirits dynamics present in the data under evaluation well.

Topographic abnormality of slow cortical potentials in schizophrenia

A recent study from our laboratory has provided evidence for the generation of slow potentials occurring in anticipation to task-performance feedback stimuli, in multiple association cortical areas, consistently including two prefrontal areas. In the present study, we intended to determine whether these slow potentials would indicate some abnormality (topographic) in schizophrenic patients, and thus serve as an indication of abnormal association cortex activity. We recorded slow potentials while subjects performed a paired-associates memory task. A 123-channel EEG montage and common average reference were used for 20 unmedicated schizophrenic (mean duration of illness: 11.3 ± 9.2 years; mean number of previous hospitalizations: 1.2 ± 1.9) and 22 healthy control subjects during a visual paired-associates matching task. For the topographic analysis, we used a simple index of individual topographic deviation from normality, corrected for absolute potential intensities. Slow potentials were observed in all subjects. Control subjects showed a simple spatial pattern of voltage extrema (left central positive and right prefrontal negative), whereas schizophrenic patients presented a more complex, fragmented pattern. Topographic deviation was significantly different between groups (P < 0.001). The increased topographic complexity in schizophrenics could be visualized in grand averages computed across subjects. Increased topographic complexity could also be seen when grand averages were computed for subgroups of patients assembled either according to task-performance (high versus low) or by their scores on psychopathological scales. There was no significant correlation between topographic deviation and psychopathology scores. We conclude that the slow potential topographic abnormalities of schizophrenia indicate an abnormality in the configuration of large-scale electrical activity in association cortices.

Analyzing the Effects of the New Renewable Energy Policy in Russia on Investments into Wind, Solar and Small Hydro Power

This thesis presents an analysis of recently enacted Russian renewable energy policy based on capacity mechanism. Considering its novelty and poor coverage by academic literature, the aim of the thesis is to analyze capacity mechanism influence on investors’ decision-making process. The current research introduces a number of approaches to investment analysis. Firstly, classical financial model was built with Microsoft Excel® and crisp efficiency indicators such as net present value were determined. Secondly, sensitivity analysis was performed to understand different factors influence on project profitability. Thirdly, Datar-Mathews method was applied that by means of Monte Carlo simulation realized with Matlab Simulink®, disclosed all possible outcomes of investment project and enabled real option thinking. Fourthly, previous analysis was duplicated by fuzzy pay-off method with Microsoft Excel®. Finally, decision-making process under capacity mechanism was illustrated with decision tree. Capacity remuneration paid within 15 years is calculated individually for each RE project as variable annuity that guarantees a particular return on investment adjusted on changes in national interest rates. Analysis results indicate that capacity mechanism creates a real option to invest in renewable energy project by ensuring project profitability regardless of market conditions if project-internal factors are managed properly. The latter includes keeping capital expenditures within set limits, production performance higher than 75% of target indicators, and fulfilling localization requirement, implying producing equipment and services within the country. Occurrence of real option shapes decision-making process in the following way. Initially, investor should define appropriate location for a planned power plant where high production performance can be achieved, and lock in this location in case of competition. After, investor should wait until capital cost limit and localization requirement can be met, after that decision to invest can be made without any risk to project profitability. With respect to technology kind, investment into solar PV power plant is more attractive than into wind or small hydro power, since it has higher weighted net present value and lower standard deviation. However, it does not change decision-making strategy that remains the same for each technology type. Fuzzy pay-method proved its ability to disclose the same patterns of information as Monte Carlo simulation. Being effective in investment analysis under uncertainty and easy in use, it can be recommended as sufficient analytical tool to investors and researchers. Apart from described results, this thesis contributes to the academic literature by detailed description of capacity price calculation for renewable energy that was not available in English before. With respect to methodology novelty, such advanced approaches as Datar-Mathews method and fuzzy pay-off method are applied on the top of investment profitability model that incorporates capacity remuneration calculation as well. Comparison of effects of two different RE supporting schemes, namely Russian capacity mechanism and feed-in premium, contributes to policy comparative studies and exhibits useful inferences for researchers and policymakers. Limitations of this research are simplification of assumptions to country-average level that restricts our ability to analyze renewable energy investment region wise and existing limitation of the studying policy to the wholesale power market that leaves retail markets and remote areas without our attention, taking away medium and small investment into renewable energy from the research focus. Elimination of these limitations would allow creating the full picture of Russian renewable energy investment profile.

Relationship between cardiovascular dysfunction and hyperglycemia in streptozotocin-induced diabetes in rats

Streptozotocin (STZ)-induced diabetes in rats is characterized by cardiovascular dysfunction beginning 5 days after STZ injection, which may reflect functional or structural autonomic nervous system damage. We investigated cardiovascular and autonomic function, in rats weighing 166 ± 4 g, 5-7, 14, 30, 45, and 90 days after STZ injection (N = 24, 33, 27, 14, and 13, respectively). Arterial pressure (AP), mean AP (MAP) variability (standard deviation of the mean of MAP, SDMMAP), heart rate (HR), HR variability (standard deviation of the normal pulse intervals, SDNN), and root mean square of successive difference of pulse intervals (RMSSD) were measured. STZ induced increased glycemia in diabetic rats vs control rats. Diabetes reduced resting HR from 363 ± 12 to 332 ± 5 bpm (P < 0.05) 5 to 7 days after STZ and reduced MAP from 121 ± 2 to 104 ± 5 mmHg (P = 0.007) 14 days after STZ. HR and MAP variability were lower in diabetic vs control rats 30-45 days after STZ injection (RMSSD decreased from 5.6 ± 0.9 to 3.4 ± 0.4 ms, P = 0.04 and SDMMAP from 6.6 ± 0.6 to 4.2 ± 0.6 mmHg, P = 0.005). Glycemia was negatively correlated with resting AP and HR (r = -0.41 and -0.40, P < 0.001) and with SDNN and SDMMAP indices (r = -0.34 and -0.49, P < 0.01). Even though STZ-diabetic rats presented bradycardia and hypotension early in the course of diabetes, their autonomic function was reduced only 30-45 days after STZ injection and these changes were negatively correlated with plasma glucose, suggesting a metabolic origin.

A routine electrocardiogram cannot be used to determine the size of myocardial infarction in the rat

Nine lead electrocardiograms of non-infarcted (N = 61) and infarcted (N = 71) female Wistar rats (200-250 g) were analyzed in order to distinguish left ventricle myocardial infarction (MI) larger than 40% (LMI) from MI smaller than 40% (SMI). MI larger than 40% clearly caused a deviation of ÂQRS and ÂT from normal values of 270-360 degrees to 90-270 degrees. Infarcted rats showed Q wave in D1 larger than 1 mm with 94% sensitivity and 100% specificity. The sum of QRS positivity in V1, V2 and V6 lower than 10 mm identified MI with 82% sensitivity and 100% specificity. The data showed that MI can be easily and reliably diagnosed by electrocardiogram in the rat. However, contradicting what is frequently believed, when specificity and sensitivity were analyzed focusing on MI size, none of these current electrocardiographic indices of MI size adequately discriminates LMI from SMI.

A semi-automatic computerized method to measure baroreflex-mediated heart rate responses that reduces interobserver variability

Arterial baroreflex sensitivity estimated by pharmacological impulse stimuli depends on intrinsic signal variability and usually a subjective choice of blood pressure (BP) and heart rate (HR) values. We propose a semi-automatic method to estimate cardiovascular reflex sensitivity to bolus infusions of phenylephrine and nitroprusside. Beat-to-beat BP and HR time series for male Wistar rats (N = 13) were obtained from the digitized signal (sample frequency = 2 kHz) and analyzed by the proposed method (PRM) developed in Matlab language. In the PRM, time series were low-pass filtered with zero-phase distortion (3rd order Butterworth used in the forward and reverse direction) and presented graphically, and parameters were selected interactively. Differences between basal mean values and peak BP (deltaBP) and HR (deltaHR) values after drug infusions were used to calculate baroreflex sensitivity indexes, defined as the deltaHR/deltaBP ratio. The PRM was compared to the method traditionally (TDM) employed by seven independent observers using files for reflex bradycardia (N = 43) and tachycardia (N = 61). Agreement was assessed by Bland and Altman plots. Dispersion among users, measured as the standard deviation, was higher for TDM for reflex bradycardia (0.60 ± 0.46 vs 0.21 ± 0.26 bpm/mmHg for PRM, P < 0.001) and tachycardia (0.83 ± 0.62 vs 0.28 ± 0.28 bpm/mmHg for PRM, P < 0.001). The advantage of the present method is related to its objectivity, since the routine automatically calculates the desired parameters according to previous software instructions. This is an objective, robust and easy-to-use tool for cardiovascular reflex studies.

Differential evolution based classification with pool of distances and aggregation operators

The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.

The effect of an aerobic training program on the electrical remodeling of the heart: high-frequency components of the signal-averaged electrocardiogram are predictors of the maximal aerobic power

Increased heart rate variability (HRV) and high-frequency content of the terminal region of the ventricular activation of signal-averaged ECG (SAECG) have been reported in athletes. The present study investigates HRV and SAECG parameters as predictors of maximal aerobic power (VO2max) in athletes. HRV, SAECG and VO2max were determined in 18 high-performance long-distance (25 ± 6 years; 17 males) runners 24 h after a training session. Clinical visits, ECG and VO2max determination were scheduled for all athletes during thew training period. A group of 18 untrained healthy volunteers matched for age, gender, and body surface area was included as controls. SAECG was acquired in the resting supine position for 15 min and processed to extract average RR interval (Mean-RR) and root mean squared standard deviation (RMSSD) of the difference of two consecutive normal RR intervals. SAECG variables analyzed in the vector magnitude with 40-250 Hz band-pass bi-directional filtering were: total and 40-µV terminal (LAS40) duration of ventricular activation, RMS voltage of total (RMST) and of the 40-ms terminal region of ventricular activation. Linear and multivariate stepwise logistic regressions oriented by inter-group comparisons were adjusted in significant variables in order to predict VO2max, with a P < 0.05 considered to be significant. VO2max correlated significantly (P < 0.05) with RMST (r = 0.77), Mean-RR (r = 0.62), RMSSD (r = 0.47), and LAS40 (r = -0.39). RMST was the independent predictor of VO2max. In athletes, HRV and high-frequency components of the SAECG correlate with VO2max and the high-frequency content of SAECG is an independent predictor of VO2max.

Effect of auditory training on the middle latency response in children with (central) auditory processing disorder

The purpose of this study was to determine the middle latency response (MLR) characteristics (latency and amplitude) in children with (central) auditory processing disorder [(C)APD], categorized as such by their performance on the central auditory test battery, and the effects of these characteristics after auditory training. Thirty children with (C)APD, 8 to 14 years of age, were tested using the MLR-evoked potential. This group was then enrolled in an 8-week auditory training program and then retested at the completion of the program. A control group of 22 children without (C)APD, composed of relatives and acquaintances of those involved in the research, underwent the same testing at equal time intervals, but were not enrolled in the auditory training program. Before auditory training, MLR results for the (C)APD group exhibited lower C3-A1 and C3-A2 wave amplitudes in comparison to the control group [C3-A1, 0.84 µV (mean), 0.39 (SD - standard deviation) for the (C)APD group and 1.18 µV (mean), 0.65 (SD) for the control group; C3-A2, 0.69 µV (mean), 0.31 (SD) for the (C)APD group and 1.00 µV (mean), 0.46 (SD) for the control group]. After training, the MLR C3-A1 [1.59 µV (mean), 0.82 (SD)] and C3-A2 [1.24 µV (mean), 0.73 (SD)] wave amplitudes of the (C)APD group significantly increased, so that there was no longer a significant difference in MLR amplitude between (C)APD and control groups. These findings suggest progress in the use of electrophysiological measurements for the diagnosis and treatment of (C)APD.