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Herry, C.

Publications and source records attributed to Herry, C..

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First evidence that intrinsic fetal heart rate variability exists and is affected by chronic hypoxia

INTRODUCTIONIt is established that normal fetal HRV represents the integration of the autonomic nervous system, components due to fetal body and breathing movements, baroreflex and circadian processes. There is also some evidence of possible intrinsic pacemaker rhythms of the SA node affecting HRV in adult disease.\n\nHowever, whether intrinsic HRV (iHRV) exists in the fetal period and whether this is affected by chronic fetal hypoxia has never been tested. Here, we show iHRV in isolated hearts from fetal sheep in late gestation and significant effects on iHRV of pregnancy complicated by chronic fetal hypoxia.\n\nMETHODSChronically catheterized ewes carrying male singleton fetuses were exposed to normoxia (n=6) or hypoxia (10% inspired O2, n=9) for the last third of gestation (105-138 dG; term~145 dG) in bespoke isobaric chambers, as before. At 138dG, isolated hearts were studied under a Langendorff preparation. CIMVA software was used to calculate basal iHRV matrix indices across five signal-analytical domains from the systolic peaks within 15 min segments in each heart, as before. Data presented as Mean+SEM were compared by the Students t test for unpaired data.\n\nRESULTSThis level of maternal H yields fetal PaO2 values of 11.5{+/-}0.6 relative to controls of 20.9{+/-}0.5 mmHg. Hearts isolated from H pregnancy showed approximately 4-fold increases in the Grid transformation feature as well as the AND similarity index (sgridAND, informational domain) and a 4-fold reduction in the Scale dependent Lyapunov exponent slope (SDLEalpha, invariant domain). We also detected a 2-fold reduction in the Recurrence quantification analysis, the percentage of laminarity and recurrences and maximum diagonal line (pL, pR, dlmax, all from geometric domain) and (AsymI, energetic domain). For dlmax and sgridAND measures, this is also correlated to left ventricular end-diastolic pressure (LVEDP) across both groups.\n\nCONCLUSIONSThe isolated fetal hearts from the hypoxic pregnancy group exhibit a lower complexity in iHRV. This is the first evidence that iHRV originates in fetal life and that chronic fetal hypoxia significantly alters it.\n\nSignificance StatementFetal heart rate variability (fHRV) is an important indicator of health and disease, yet its physiological origins are poorly understood. Both, the heart, intrinsically, and extrinsic systems, such as the brain, are hypothesized to contribute to HRV. In a near-term fetal sheep model of human development, we identified fHRV components reflecting intrinsic contributions to fHRV. In addition, we show that these intrinsic fHRV components carry memory of chronic oxygen deprivation the fetus experienced during the last third of gestation.

physiology

Real-time changepoint detection for noisy biological time series

Experimentally and clinically collected time series data are often contaminated with significant confounding noise, creating short, noisy time series. This noise, due to natural variability and measurement error, poses a challenge to conventional change point detection methods.\n\nWe propose a novel and robust statistical method for change point detection for noisy biological time sequences. Our method is a significant improvement over traditional change point detection methods, which only examine a potential anomaly at a single time point. In contrast, our method considers all suspected anomaly points and considers the joint probability distribution of the number of change points and the elapsed time between two consecutive anomalies. We validate our method with three simulated time series, a widely accepted benchmark data set, two geological time series, a data set of ECG recordings, and a physiological data set of heart rate variability measurements of fetal sheep model of human labour, comparing it to three existing methods. Our method demonstrates significantly improved performance over the existing pointwise detection methods.

bioinformatics