PhysioZoo: A Novel Open Access Platform for Heart Rate Variability Analysis of Mammalian Electrocardiographic Data

Background: The time variation between consecutive heartbeats is commonly referred to as heart rate variability (HRV). Loss of complexity in HRV has been documented in several cardiovascular diseases and has been associated with an increase in morbidity and mortality. However, the mechanisms that control HRV are not well understood. Animal experiments are the key to investigating this question. However, to date, there are no standard open source tools for HRV analysis of mammalian electrocardiogram (ECG) data and no centralized public databases for researchers to access.Methods: We created an open source software solution specifically designed for HRV analysis from ECG data of multiple mammals, including humans. We also created a set of public databases of mammalian ECG signals (dog, rabbit and mouse) with manually corrected R-peaks (>170,000 annotations) and signal quality annotations. The platform (software and databases) is called PhysioZoo.Results: PhysioZoo makes it possible to load ECG data and perform very accurate R-peak detection (F1 > 98%). It also allows the user to manually correct the R-peak locations and annotate low signal quality of the underlying ECG. PhysioZoo implements state of the art HRV measures adapted for different mammals (dogs, rabbits, and mice) and allows easy export of all computed measures together with standard data representation figures. PhysioZoo provides databases and standard ranges for all HRV measures computed on healthy, conscious humans, dogs, rabbits, and mice at rest. Study of these measures across different mammals can provide new insights into the complexity of heart rate dynamics across species.Conclusion: PhysioZoo enables the standardization and reproducibility of HRV analysis in mammalian models through its open source code, freely available software, and open access databases. PhysioZoo will support and enable new investigations in mammalian HRV research. The source code and software are available on www.physiozoo.com

Distinct PKA Signaling in Cytosolic and Mitochondrial Compartments in Electrically Paced Atrial Myocytes

Protein kinase A (PKA) is a key nodal signaling molecule that regulates a wide range of cellular functions in the cytosol and mitochondria. The distribution of A-kinase anchoring proteins that tether PKA, the local interaction with degradation molecules, and regulation by Ca2+, may lead to distinct spatiotemporal cAMP/PKA signaling in these compartments. In this work, FRET-based sensors were used to investigate PKA signaling in the cytosol, outer mitochondrial membrane (OMM), and mitochondrial matrix (MM) and its crosstalk with Ca2+ in response to electrical stimulation of cultured rabbit atrial cells. A gradual decrease in PKA activity eliminating the ability of the atrial cells to respond to physiological electrical stimulation, was observed upon treatment of cells with H-89. Chelation of intracellular Ca2+ by BAPTA reduced PKA activity and diminished its response to forskolin, an AC stimulator. Under basal conditions, PKA activity in response to forskolin was lower in the OMM compared to the cytosol and MM. In response to electrical stimulation in the presence of ISO, distinct compartmentalization of PKA activity was observed, with higher activity in the cytosol and MM than in the OMM. Thus, distinct Ca2+-dependent spatiotemporal cAMP/PKA signaling exists in atrial cells, likely mediating its excitation and mitochondrial function

Signatures of the autonomic nervous system and the heart’s pacemaker cells in canine electrocardiograms and their applications to humans

Abstract Heart rate and heart rate variability (HRV) are mainly determined by the autonomic nervous system (ANS), which interacts with receptors on the sinoatrial node (SAN; the heart’s primary pacemaker), and by the “coupled-clock” system within the SAN cells. HRV changes are associated with cardiac diseases. However, the relative contributions of the ANS and SAN to HRV are not clear, impeding effective treatment. To discern the SAN’s contribution, we performed HRV analysis on canine electrocardiograms containing basal and ANS-blockade segments. We also analyzed human electrocardiograms of atrial fibrillation and heart failure patients, as well as healthy aged subjects. Finally, we used a mathematical model to simulate HRV under decreased “coupled-clock” regulation. We found that (a) in canines, the SAN and ANS contribute mainly to long- and short-term HRV, respectively; (b) there is evidence suggesting a similar relative SAN contribution in humans; (c) SAN features can be calculated from beat-intervals obtained in-vivo, without intervention; (d) ANS contribution can be modeled by sines embedded in white noise; (e) HRV changes associated with cardiac diseases and aging can be interpreted as deterioration of both SAN and ANS; and (f) SAN clock-coupling can be estimated from changes in HRV. This may enable future non-invasive diagnostic applications

Age-dependent contribution of intrinsic mechanisms to sinoatrial node function in humans

Abstract Average beat interval (BI) and beat interval variability (BIV) are primarily determined by mutual entrainment between the autonomic-nervous system (ANS) and intrinsic mechanisms that govern sinoatrial node (SAN) cell function. While basal heart rate is not affected by age in humans, age-dependent reductions in intrinsic heart rate have been documented even in so-called healthy individuals. The relative contributions of the ANS and intrinsic mechanisms to age-dependent deterioration of SAN function in humans are not clear. We recorded ECG on patients (n = 16 < 21 years and n = 23 41–78 years) in the basal state and after ANS blockade (propranolol and atropine) in the presence of propofol and dexmedetomidine anesthesia. Average BI and BIV were analyzed. A set of BIV features were tested to designated the “signatures” of the ANS and intrinsic mechanisms and also the anesthesia “signature”. In young patients, the intrinsic mechanisms and ANS mainly contributed to long- and short-term BIV, respectively. In adults, both ANS and intrinsic mechanisms contributed to short-term BIV, while the latter also contributed to long-term BIV. Furthermore, anesthesia affected ANS function in young patients and both mechanisms in adult. The work also showed that intrinsic mechanism features can be calculated from BIs, without intervention