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Gee MM, Hornung E, Gupta S, Newton AJH, Cheng ZJ, Lytton WW, Lenhoff AM, Schwaber JS, Vadigepalli R. Unpacking the multimodal, multi-scale data of the fast and slow lanes of the cardiac vagus through computational modelling. Exp Physiol 2023:10.1113/EP090865. [PMID: 37120805 PMCID: PMC10613580 DOI: 10.1113/ep090865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 04/12/2023] [Indexed: 05/01/2023]
Abstract
NEW FINDINGS What is the topic of this review? The vagus nerve is a crucial regulator of cardiovascular homeostasis, and its activity is linked to heart health. Vagal activity originates from two brainstem nuclei: the nucleus ambiguus (fast lane) and the dorsal motor nucleus of the vagus (slow lane), nicknamed for the time scales that they require to transmit signals. What advances does it highlight? Computational models are powerful tools for organizing multi-scale, multimodal data on the fast and slow lanes in a physiologically meaningful way. A strategy is laid out for how these models can guide experiments aimed at harnessing the cardiovascular health benefits of differential activation of the fast and slow lanes. ABSTRACT The vagus nerve is a key mediator of brain-heart signaling, and its activity is necessary for cardiovascular health. Vagal outflow stems from the nucleus ambiguus, responsible primarily for fast, beat-to-beat regulation of heart rate and rhythm, and the dorsal motor nucleus of the vagus, responsible primarily for slow regulation of ventricular contractility. Due to the high-dimensional and multimodal nature of the anatomical, molecular and physiological data on neural regulation of cardiac function, data-derived mechanistic insights have proven elusive. Elucidating insights has been complicated further by the broad distribution of the data across heart, brain and peripheral nervous system circuits. Here we lay out an integrative framework based on computational modelling for combining these disparate and multi-scale data on the two vagal control lanes of the cardiovascular system. Newly available molecular-scale data, particularly single-cell transcriptomic analyses, have augmented our understanding of the heterogeneous neuronal states underlying vagally mediated fast and slow regulation of cardiac physiology. Cellular-scale computational models built from these data sets represent building blocks that can be combined using anatomical and neural circuit connectivity, neuronal electrophysiology, and organ/organismal-scale physiology data to create multi-system, multi-scale models that enable in silico exploration of the fast versus slow lane vagal stimulation. The insights from the computational modelling and analyses will guide new experimental questions on the mechanisms regulating the fast and slow lanes of the cardiac vagus toward exploiting targeted vagal neuromodulatory activity to promote cardiovascular health.
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Affiliation(s)
- Michelle M Gee
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE, USA
- Department of Pathology and Genomic Medicine, Daniel Baugh Institute of Functional Genomics/Computational Biology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Eden Hornung
- Department of Pathology and Genomic Medicine, Daniel Baugh Institute of Functional Genomics/Computational Biology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Suranjana Gupta
- Department of Physiology and Pharmacology, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Adam J H Newton
- Department of Physiology and Pharmacology, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Zixi Jack Cheng
- Burnett School of Biomedical Sciences, College of Medicine, University of Central Florida, Orlando, FL, USA
| | - William W Lytton
- Department of Physiology and Pharmacology, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Abraham M Lenhoff
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE, USA
| | - James S Schwaber
- Department of Pathology and Genomic Medicine, Daniel Baugh Institute of Functional Genomics/Computational Biology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Rajanikanth Vadigepalli
- Department of Pathology and Genomic Medicine, Daniel Baugh Institute of Functional Genomics/Computational Biology, Thomas Jefferson University, Philadelphia, PA, USA
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Gee MM, Lenhoff AM, Schwaber JS, Ogunnaike BA, Vadigepalli R. Closed-loop modeling of central and intrinsic cardiac nervous system circuits underlying cardiovascular control. AIChE J 2023; 69:e18033. [PMID: 37250861 PMCID: PMC10211393 DOI: 10.1002/aic.18033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 01/02/2023] [Indexed: 01/16/2023]
Abstract
The baroreflex is a multi-input, multi-output control physiological system that regulates blood pressure by modulating nerve activity between the brainstem and the heart. Existing computational models of the baroreflex do not explictly incorporate the intrinsic cardiac nervous system (ICN), which mediates central control of the heart function. We developed a computational model of closed-loop cardiovascular control by integrating a network representation of the ICN within central control reflex circuits. We examined central and local contributions to the control of heart rate, ventricular functions, and respiratory sinus arrhythmia (RSA). Our simulations match the experimentally observed relationship between RSA and lung tidal volume. Our simulations predicted the relative contributions of the sensory and the motor neuron pathways to the experimentally observed changes in the heart rate. Our closed-loop cardiovascular control model is primed for evaluating bioelectronic interventions to treat heart failure and renormalize cardiovascular physiology.
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Affiliation(s)
- Michelle M Gee
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE 19716
- Daniel Baugh Institute of Functional Genomics/Computational Biology, Department of Pathology and Genomic Medicine, Thomas Jefferson University, Philadelphia, PA 19107
| | - Abraham M Lenhoff
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE 19716
| | - James S Schwaber
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE 19716
- Daniel Baugh Institute of Functional Genomics/Computational Biology, Department of Pathology and Genomic Medicine, Thomas Jefferson University, Philadelphia, PA 19107
| | - Babatunde A Ogunnaike
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE 19716
| | - Rajanikanth Vadigepalli
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE 19716
- Daniel Baugh Institute of Functional Genomics/Computational Biology, Department of Pathology and Genomic Medicine, Thomas Jefferson University, Philadelphia, PA 19107
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