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Intracranial hemorrhage (IH) is a major problem of neonatal intensive care. The incidence of IH is typically asymptomatic and cannot be effectively detected by standard diagnostic methods. The mechanisms underlying IH are unknown but there is evidence that stress-induced disorders in adrenergic regulation of cerebral venous blood flow (CVBF) are among the main reasons. Quantitative and qualitative assessment of CVBF could significantly advance understanding of the nature of IH in newborns. In this work, we analyze variations of CVBF in newborn rats with an experimental model of stress-induced IH and adrenaline injection. Our analysis is based on the Doppler optical coherence tomography (DOCT) and a proposed adaptive wavelet-based approach that provides sensitive markers of abnormal reactions of the sagittal vein to external factors. The obtained results demonstrate that the incidence of IH in newborn rats is accompanied by a suppression of CVBF with the development of venous insufficiency and areactivity to adrenaline. We introduce a numerical measure θ, quantifying reactions of CVBF and show that the values θ < 1.23 estimated in the low-frequency (LF) spectral range corresponding to the sympathicus indicate abnormal reactions associated with the development of IH. We conclude that the revealed areactivity of the cerebral veins to adrenaline represents a possible mechanism responsible for pathological changes in CVBF. [ABSTRACT FROM AUTHOR]

The purpose of this study is to demonstrate the possibility of revealing new characteristic features of renal blood flow autoregulation in healthy and pathological states through the application of discrete wavelet transforms to experimental time series for normotensive and hypertensive rats. A reduction in the variability of the wavelet coefficients in hypertension is observed at both the microscopic level of the blood flow in efferent arterioles of individual nephrons and at the macroscopic level of the blood pressure in the main arteries. The reduction is manifest in both of the main frequency domains of nephron autoregulation and is likely to reflect a reduced flexibility of the cardiovascular system during hypertension. [ABSTRACT FROM AUTHOR]

We searched for synchronization among autoregulation mechanisms using wavelet transforms applied to tubular pressure recordings in nephron pairs from the surface of rat kidneys. Nephrons have two oscillatory modes in the regulation of their pressures and flows: a faster (100-200 mHz) myogenic mode, and a slower (20-40 mHz) oscillation in tubuloglomerular feedback (TGF). These mechanisms interact; the TGF mode modulates both the amplitude and the frequency of the myogenic mode. Nephrons also communicate with each other using vascular signals triggered by membrane events in arteriolar smooth muscle cells. In addition, the TGF oscillation changes in hypertension to an irregular fluctuation with characteristics of deterministic chaos. The analysis shows that, within single nephrons of normotensive rats, the myogenic mode and TGF are synchronized at discrete frequency ratios, with 5:1 most common. There is no distinct synchronization ratio in spontaneously hypertensive rats (SHR). In normotensive rats, full synchronization of both TGF and myogenic modes is the most probable state for pairs of nephrons originating in a common cortical radial artery. For SHR, full synchronization is less probable; most common in SHR is a state of partial synchronization with entrainment between neighboring nephrons for only one of the modes. Modulation of the myogenic mode by the TGF mode is much stronger in hypertensive than in normotensive rats. Synchronization among nephrons forms the basis for an integrated reaction to blood pressure fluctuations. Reduced synchronization in SHR suggests that the effectiveness of the coordinated response is impaired in hypertension. [ABSTRACT FROM AUTHOR]

The article makes use of three different examples (sensory information processing in the rat trigeminal complex, intracellular interaction in snail neurons and multimodal dynamics in nephron autoregulation) to demonstrate how modern approaches to time-series analysis based on the wavelet-transform can provide information about the underlying complex biological processes. [ABSTRACT FROM AUTHOR]