A novel quantitative method for diabetic cardiac autonomic neuropathy assessment in type 1 diabetic mice.

In this work, we used a sensitive and noninvasive computational method to assess diabetic cardiovascular autonomic neuropathy (DCAN) from pulse oximeter (photoplethysmographic; PPG) recordings from mice. The method, which could be easily applied to humans, is based on principal dynamic mode (PDM) analysis of heart rate variability (HRV). Unlike the power spectral density, PDM has been shown to be able to separately identify the activities of the parasympathetic and sympathetic nervous systems without pharmacological intervention. HRV parameters were measured by processing PPG signals from conscious 1.5- to 5-month-old C57/BL6 control mice and in Akita mice, a model of insulin-dependent type 1 diabetes, and compared with the gold-standard Western blot and immunohistochemical analyses. The PDM results indicate significant cardiac autonomic impairment in the diabetic mice in comparison to the controls. When tail-cuff PPG recordings were collected and analyzed starting from 1.5 months of age in both C57/Bl6 controls and Akita mice, onset of DCAN was seen at 3 months in the Akita mice, which persisted up to the termination of the recording at 5 months. Western blot and immunohistochemical analyses also showed a reduction in nerve density in Akita mice at 3 and 4 months as compared to the control mice, thus, corroborating our PDM data analysis of HRV records. Western blot analysis of autonomic nerve proteins corroborated the PPG-based HRV analysis via the PDM approach. In contrast, traditional HRV analysis (based on either the power spectral density or time-domain measures) failed to detect the nerve rarefaction.

Time-frequency approaches for the detection of interactions and temporal properties in renal autoregulation.

We compare the influence of time-frequency methods on analysis of time-varying renal autoregulation properties. Particularly, we examine if detection probabilities are similar for amplitude and frequency modulation for a modulated simulation signal among five time-frequency approaches, and if time-varying changes in system gain are detected using four approaches for estimating time-varying transfer functions. Detection of amplitude and frequency modulation varied among methods and was dependent upon background noise added to the simulated data. Three non-parametric time-frequency methods accurately detected modulation at low frequencies across noise levels but not high frequencies; while the converse was true for a fourth, and a fifth non-parametric approach was not capable of modulation detection. When applied to estimation of time-varying transfer functions, the parametric approach provided the most accurate estimations of system gain changes, detecting a 1 dB step increase. Application of the appropriate methods to laser Doppler recordings of cortical blood flow and arterial pressure data in anesthetized rats reaffirm the presence of time-varying dynamics in renal autoregulation. An increase in the peak system gain and detection of amplitude modulation of the Myogenic mechanism both occurred after inhibition of nitric oxide synthase, suggesting a connection between the operation of underlying regulators and system performance.

Role of uncoupled endothelial nitric oxide synthase in abdominal aortic aneurysm formation: treatment with folic acid.

It has been shown that endothelial NO synthase (eNOS) uncoupling occurs in hypertension and atherosclerosis. However, its causal role in vascular pathogenesis has not been characterized previously. Here, we challenged eNOS preuncoupled hyperphenylalaninemia (hph)-1 mice (deficient in eNOS cofactor tetrahydrobiopterin biosynthetic enzyme GTPCHI) with angiotensin II (Ang II; 0.7 mg/kg per day, 14 days). Both wild-type and hph-1 groups developed hypertension similarly up to day 6 to 7. Thereafter, ≈14% of Ang II-infused (0.7 mg/kg per day) hph-1 mice (n=72) started to die suddenly of ruptured abdominal aortic aneurysm (AAA). Among the survivors, 65% developed AAA, resulting in a total morbidity rate of 79%. In contrast, none of the Ang II-infused wild-type mice died or developed AAA. Ang II progressively deteriorated eNOS uncoupling in hph-1 mice while augmenting tetrahydrobiopterin and nitric oxide (NO(·)) deficiencies. The abundance of the tetrahydrobiopterin salvage enzyme dihydrofolate reductase in the endothelium was decreased in hph-1 mice and further diminished by Ang II infusion. Intriguingly, restoration of dihydrofolate reductase expression by oral administration of folic acid or overexpression of dihydrofolate reductase completely prevented AAA formation in Ang II-infused hph-1 mice while attenuating progressive uncoupling of eNOS. Folic acid also attenuated vascular remodeling and inflammation characterized by medial elastin breakdown and augmented matrix metalloproteinase 2 activity and activation of matrix metalloproteinase 9, as well as macrophage infiltration. In conclusion, these data innovatively suggest a causal role of eNOS uncoupling/tetrahydrobiopterin deficiency in AAA formation. Therefore, oral folic acid administration, endothelium-targeted dihydrofolate reductase gene therapy, and perhaps other countermeasures directed against eNOS uncoupling could be used as new therapeutics for AAA.

On the efficacy of the combined use of the cross-bicoherence with surrogate data technique to statistically quantify the presence of nonlinear interactions.

The cross-bispectrum is an approach to detect the presence of quadratic phase coupling (QPC) between different components in bivariate signals. Quantification of QPC is by means of the cross-bicoherence index (CBI). The major limitations of the CBI are that it favors only the strongly coupled signals and its accuracy becomes compromised with noise and low coupling strength. To overcome this limitation, a statistical approach which combines CBI with a surrogate data method to determine the statistical significance of the QPC derived from bivariate signals is introduced. We demonstrate the accuracy of the proposed approach using simulation examples which are designed to test its robustness against noise contamination as well as varying levels of phase coupling and data lengths. Comparisons were made to the traditional CBI and the method based on the use of cross-bispectrum followed by a surrogate data technique. Our results show that the cross-bicoherence with surrogate data technique outperforms the two other methods compared in both sensitivity and specificity, and provides an unbiased and statistical approach to determining the presence of QPC in bivariate signals. These results are in contrast to our recent study where the auto-bispectrum combined with surrogate data approach had the best performance. Application of this approach to renal hemodynamic data was applied to renal stop flow pressure data obtained in the nephrons of the normotensive (N = 18) and hypertensive (N = 15) rats. We found significant nonlinear interactions between nephrons only when they are derived from the same cortical renal artery. The accuracy was 100% and verified by comparing the results to the known vascular connectivity between nephrons.

Nonlinear coupling is absent in acute myocardial patients but not healthy subjects.

We investigated whether autonomic nervous system imbalance imposed by pharmacological blockades and associated with acute myocardial infarction (AMI) is manifested as modifications of the nonlinear interactions in heart rate variability signal using a statistically based bispectrum method. The statistically based bispectrum method is an ideal approach for identifying nonlinear couplings in a system and overcomes the previous limitation of determining in an ad hoc way the presence of such interactions. Using the improved bispectrum method, we found significant nonlinear interactions in healthy young subjects, which were abolished by the administration of atropine but were still present after propranolol administration. The complete decoupling of nonlinear interactions was obtained with double pharmacological blockades. Nonlinear couplings were found to be the strongest for healthy young subjects followed by degradation with old age and a complete absence of such couplings for the old age-matched AMI subjects. Our results suggest that the presence of nonlinear couplings is largely driven by the parasympathetic nervous system regulation and that the often-reported autonomic nervous system imbalance seen in AMI subjects is manifested as the absence of nonlinear interactions between the sympathetic and parasympathetic nervous regulations.

Statistical approach to quantify the presence of phase coupling using the bispectrum.

The bispectrum is a method to detect the presence of phase coupling between different components in a signal. The traditional way to quantify phase coupling is by means of the bicoherence index, which is essentially a normalized bispectrum. The major drawback of the bicoherence index (BCI) is that determination of significant phase coupling becomes compromised with noise and low coupling strength. To overcome this limitation, a statistical approach that combines the bispectrum with a surrogate data method to determine the statistical significance of the phase coupling is introduced. Our method does not rely on the use of the BCI, where the normalization procedure of the BCI is the major culprit in its poor specificity. We demonstrate the accuracy of the proposed approach using simulation examples that are designed to test its robustness against noise contamination as well as varying levels of phase coupling. Our results show that the proposed approach outperforms the bicoherence index in both sensitivity and specificity and provides an unbiased and statistical approach to determining the presence of quadratic phase coupling. Application of this new method to renal hemodynamic data was applied to renal stop flow pressure data obtained from normotensive (N = 7) and hypertensive (N = 7) rats. We found significant nonlinear interactions in both strains of rats with a greater magnitude of coupling and smaller number of interaction peaks in normotensive rats than hypertensive rats.

Very low frequency modulation in renal autoregulation.

This study aims to examine the presence of a possible third renal autoregulatory mechanism in the very low frequency (VLF) band (approximately 10 mHz) using a high-resolution time- frequency spectral method. Blood pressure and renal blood flow data were measured from conscious and anesthetized Sprague-Dawley and spontaneously hypertensive rats, at the level of the whole kidney (via ultrasound flow probe) and local cortical tissue of a kidney (via laser Doppler flow probe). In addition, N-nitro-L-arginine (LNAME) was used in order to assess the effect of nitric oxide on the third mechanism. Using a complex demodulation method with high time and frequency resolution, a VLF band was often observed, as well as amplitude modulation at the VLF of the two other autoregulation mechanisms. The presence of amplitude modulation is an indication of a particular form of nonlinear interaction between the autoregulatory mechanisms. Physically, such interactions may arise from the fact that all three mechanisms share a common effector, the afferent arteriole. In addition, the magnitude of amplitude modulation of the VLF on the other autoregulatory mechanisms was enhanced by the addition of LNAME, suggesting an important role of nitric oxide in the autoregulatory process.