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Surrogate data analysis of renal tubular pressure fluctuations in hypertensive rats

机译:高血压大鼠肾小管压力波动的替代数据分析

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Abstract: We observed previously that hydraulic pressure in rat renal proximal tubules changes from the periodic oscillations found in normal animals to random-appearing fluctuations during the development of hypertension. It was suggested that the random- appearing fluctuations seen in the hypertensive rats were due to chaotic dynamics in the systems regulating tubular pressure and flow. To test this hypothesis we have now produced surrogate data sets from the originals by randomizing the phase of the power spectra. We have applied both correlation dimension estimation and forecasting error as discriminating statistics. The results show that the original experimental time series can be distinguished from linear and static nonlinear correlated noise, which confirms that the nonlinear behavior is due to the intrinsic dynamics of the system. This finding suggests that there is a low dimensional chaotic attractor that governs renal hemodynamics in the hypertensive stage. To our knowledge this represents the first rigorous demonstration of a transition to chaotic dynamics in an integrated physiological control system occurring in association with a pathological condition.!18
机译:摘要:我们先前观察到,大鼠肾脏近端小管中的液压从正常动物中发现的周期性振荡变化为高血压发展过程中随机出现的波动。有人认为,在高血压大鼠中出现的随机出现的波动是由于调节肾小管压力和流量的系统中的混沌动力学引起的。为了检验这个假设,我们现在通过随机化功率谱的相位从原始数据中生成替代数据集。我们已经应用了相关维数估计和预测误差作为区分统计量。结果表明,原始的实验时间序列可以与线性和静态非线性相关噪声区分开,这证实了非线性行为是由于系统的固有动力学引起的。这一发现表明,存在一个低维混沌吸引子,它可以控制高血压期的肾脏血液动力学。据我们所知,这是与病理条件相关的综合生理控制系统向混沌动力学过渡的第一个严格证明。18

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