Intravenous ivabradine augments the dynamic heart rate response to moderate vagal nerve stimulation in anesthetized rats

Ivabradine is a selective bradycardic agent that reduces the heart rate (HR) by inhibiting the hyperpolarization-activated cyclic nucleotide-gated channels. Although its cardiovascular effect is thought to be minimal except for inducing bradycardia, ivabradine could interact with cardiovascular regulation by the autonomic nervous system. We tested whether ivabradine modifies dynamic characteristics of peripheral vagal HR control. In anesthetized Wistar-Kyoto rats ( n = 7), the right vagal nerve was sectioned and stimulated for 10 min according to a binary white noise sequence with a switching interval of 500 ms. The efferent vagal nerve stimulation (VNS) trials were performed using three different rates (10, 20, and 40 Hz), and were designated as V0–10, V0–20, and V0–40, respectively. The transfer function from the VNS to the HR was estimated before and after the intravenous administration of ivabradine (2 mg/kg). Ivabradine increased the asymptotic dynamic gain in V0–20 [from 3.88 (1.78–5.79) to 6.62 (3.12–8.31) beats·min−1·Hz−1, P < 0.01, median (range)] but not in V0–10 or V0–40. Ivabradine increased the corner frequency in V0–10 [from 0.032 (0.026–0.041) to 0.064 (0.029–0.090) Hz, P < 0.01] and V0–20 [from 0.040 (0.037–0.056) to 0.068 (0.051–0.100) Hz, P < 0.01] but not in V0–40. In conclusion, ivabradine augmented the dynamic HR response to moderate VNS. At high VNS, however, ivabradine did not significantly augment the dynamic HR response, possibly because ivabradine reduced the baseline HR and limited the range for the bradycardic response to high VNS. NEW & NOTEWORTHY Ivabradine is considered to be a pure bradycardic agent that has little effect on cardiovascular function except inducing bradycardia. The present study demonstrated that ivabradine interacts with the dynamic vagal heart rate control in a manner that augments the heart rate response to moderate-intensity efferent vagal nerve stimulation.

Adaptive Two-stage Kalman Filter for SINS/Odometer Integrated Navigation Systems

In Strapdown Inertial Navigation System (SINS)/Odometer (OD) integrated navigation systems, OD scale factor errors change with roadways and vehicle loads. In addition, the random noises of gyros and accelerometers tend to vary with time. These factors may cause the Kalman filter to be degraded or even diverge. To address this problem and reduce the computation load, an Adaptive Two-stage Kalman Filter (ATKF) for SINS/OD integrated navigation systems is proposed. In the Two-stage Kalman Filter (TKF), only the innovation in the bias estimator is a white noise sequence with zero-mean while the innovation in the bias-free estimator is not zero-mean. Based on this fact, a novel algorithm for computing adaptive factors is presented. The proposed ATKF is evaluated in a SINS/OD integrated navigation system, and the simulation results show that it is effective in estimating the change of the OD scale factor error and robust to the varying process noises. A real experiment is carried out to further validate the performance of the proposed algorithm.

Time Series Analysis of Pulmonary Tuberculosis Incidence: Forecasting by Applying the Time Series Model

The main objective of this study is to identify the stochastic autoregressive integrated moving average (ARIMA) model to predict the pulmonary tuberculosis incidence in Qianan. Considering the Box-Jenkins modeling approach, the incidence of pulmonary tuberculosis was collected monthly from 2004 to 2010. The model ARIMA(0,1,1)12 was established finally and the residual sequence was a white noise sequence. Then, this model was used for calculating dengue incidence for the last 6 observations compared with observed data, and performed to predict the monthly incidence in 2011. It is necessary and practical to apply the approach of ARIMA model in fitting time series to predict pulmonary tuberculosis within a short lead time.

Predictive Efficiency Comparison of ARIMA-Time-Series and the Grey System GM(1,1) Forecast Model on Forecasting the Incidence Rate of Hepatitis B

To compare the stochastic autoregressive integrated moving average (ARIMA) model and the grey system GM(1,1) model to predict the hepatitis B incidence in Qianan. Considering the Box-Jenkins modeling and GM(1,1) model approach, hepatitis B incidence was collected monthly from 2004 to 2011, a SARIMA model and a gray system GM(1,1) model were fit. Then, these models were used for calculating hepatitis B incidence for the last 6 observations compared with observed data. The constructed models were performed to predict the monthly incidence rate in 2013. The model SARIMA(0,1,1)(0,1,1)12 and was established finally and the residual sequence was a white noise sequence. Using Excel 2003 to establish the gray system GM(1,1) model of hepatitis B incidence and evaluating the accuracy of the mode as well as forecasting. By posterior-error-test (C=0.435, p=0.821) and residual test, the model accuracy was qualified. It was necessary and practical to apply the approach of ARIMA model in fitting time series to predict hepatitis within a short lead time. The prediction results showed that the hepatitis B incidence in 2013 had a slight upward trend.

Effects of neuronal norepinephrine uptake blockade on baroreflex neural and peripheral arc transfer characteristics

Neuronal uptake is the most important mechanism by which norepinephrine (NE) is removed from the synaptic clefts at sympathetic nerve terminals. We examined the effects of neuronal NE uptake blockade on the dynamic sympathetic regulation of the arterial baroreflex because dynamic characteristics are important for understanding the system behavior in response to exogenous disturbance. We perturbed intracarotid sinus pressure (CSP) according to a binary white noise sequence in anesthetized rabbits, while recording cardiac sympathetic nerve activity (SNA), arterial pressure (AP), and heart rate (HR). Intravenous administration of desipramine (1 mg/kg) decreased the normalized gain of the neural arc transfer function from CSP to SNA relative to untreated control (1.03 ± 0.09 vs. 0.60 ± 0.08 AU/mmHg, mean ± SE, P < 0.01) but did not affect that of the peripheral arc transfer function from SNA to AP (1.10 ± 0.05 vs. 1.08 ± 0.10 mmHg/AU). The normalized gain of the transfer function from SNA to HR was unaffected (1.01 ± 0.04 vs. 1.09 ± 0.12 beats·min−1·AU−1). Desipramine decreased the natural frequency of the transfer function from SNA to AP by 28.7 ± 7.0% (0.046 ± 0.007 vs. 0.031 ± 0.002 Hz, P < 0.05) and that of the transfer function from SNA to HR by 64.4 ± 2.2% (0.071 ± 0.003 vs. 0.025 ± 0.002 Hz, P < 0.01). In conclusion, neuronal NE uptake blockade by intravenous desipramine administration reduced the total buffering capacity of the arterial baroreflex mainly through its action on the neural arc. The differential effects of neuronal NE uptake blockade on the dynamic AP and HR responses to SNA may provide clues for understanding the complex pathophysiology of cardiovascular diseases associated with neuronal NE uptake deficiency.