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Dynamics of ventilatory pattern variability and Cardioventilatory Coupling during systemic inflammation in rats
Introduction: Biometrics of common physiologic signals can reflect health status. We have developed analytics to measure the predictability of ventilatory pattern variability (VPV, Nonlinear Complexity Index (NLCI) that quantifies the predictability of a continuous waveform associated with inhalatio...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10423997/ https://www.ncbi.nlm.nih.gov/pubmed/37583625 http://dx.doi.org/10.3389/fnetp.2023.1038531 |
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author | Campanaro, Cara K. Nethery, David E. Guo, Fei Kaffashi, Farhad Loparo, Kenneth A. Jacono, Frank J. Dick, Thomas E. Hsieh, Yee-Hsee |
author_facet | Campanaro, Cara K. Nethery, David E. Guo, Fei Kaffashi, Farhad Loparo, Kenneth A. Jacono, Frank J. Dick, Thomas E. Hsieh, Yee-Hsee |
author_sort | Campanaro, Cara K. |
collection | PubMed |
description | Introduction: Biometrics of common physiologic signals can reflect health status. We have developed analytics to measure the predictability of ventilatory pattern variability (VPV, Nonlinear Complexity Index (NLCI) that quantifies the predictability of a continuous waveform associated with inhalation and exhalation) and the cardioventilatory coupling (CVC, the tendency of the last heartbeat in expiration to occur at preferred latency before the next inspiration). We hypothesized that measures of VPV and CVC are sensitive to the development of endotoxemia, which evoke neuroinflammation. Methods: We implanted Sprague Dawley male rats with BP transducers to monitor arterial blood pressure (BP) and recorded ventilatory waveforms and BP simultaneously using whole-body plethysmography in conjunction with BP transducer receivers. After baseline (BSLN) recordings, we injected lipopolysaccharide (LPS, n = 8) or phosphate buffered saline (PBS, n =3) intraperitoneally on 3 consecutive days. We recorded for 4–6 h after the injection, chose 3 epochs from each hour and analyzed VPV and CVC as well as heart rate variability (HRV). Results: First, the responses to sepsis varied across rats, but within rats the repeated measures of NLCI, CVC, as well as respiratory frequency (fR), HR, BP and HRV had a low coefficient of variation, (<0.2) at each time point. Second, HR, fR, and NLCI increased from BSLN on Days 1–3; whereas CVC decreased on Days 2 and 3. In contrast, changes in BP and the relative low-(LF) and high-frequency (HF) of HRV were not significant. The coefficient of variation decreased from BSLN to Day 3, except for CVC. Interestingly, NLCI increased before fR in LPS-treated rats. Finally, we histologically confirmed lung injury, systemic inflammation via ELISA and the presence of the proinflammatory cytokine, IL-1β, with immunohistochemistry in the ponto-medullary respiratory nuclei. Discussion: Our findings support that NLCI reflects changes in the rat’s health induced by systemic injection of LPS and reflected in increases in HR and fR. CVC decreased over the course to the experiment. We conclude that NLCI reflected the increase in predictability of the ventilatory waveform and (together with our previous work) may reflect action of inflammatory cytokines on the network generating respiration. |
format | Online Article Text |
id | pubmed-10423997 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104239972023-08-15 Dynamics of ventilatory pattern variability and Cardioventilatory Coupling during systemic inflammation in rats Campanaro, Cara K. Nethery, David E. Guo, Fei Kaffashi, Farhad Loparo, Kenneth A. Jacono, Frank J. Dick, Thomas E. Hsieh, Yee-Hsee Front Netw Physiol Network Physiology Introduction: Biometrics of common physiologic signals can reflect health status. We have developed analytics to measure the predictability of ventilatory pattern variability (VPV, Nonlinear Complexity Index (NLCI) that quantifies the predictability of a continuous waveform associated with inhalation and exhalation) and the cardioventilatory coupling (CVC, the tendency of the last heartbeat in expiration to occur at preferred latency before the next inspiration). We hypothesized that measures of VPV and CVC are sensitive to the development of endotoxemia, which evoke neuroinflammation. Methods: We implanted Sprague Dawley male rats with BP transducers to monitor arterial blood pressure (BP) and recorded ventilatory waveforms and BP simultaneously using whole-body plethysmography in conjunction with BP transducer receivers. After baseline (BSLN) recordings, we injected lipopolysaccharide (LPS, n = 8) or phosphate buffered saline (PBS, n =3) intraperitoneally on 3 consecutive days. We recorded for 4–6 h after the injection, chose 3 epochs from each hour and analyzed VPV and CVC as well as heart rate variability (HRV). Results: First, the responses to sepsis varied across rats, but within rats the repeated measures of NLCI, CVC, as well as respiratory frequency (fR), HR, BP and HRV had a low coefficient of variation, (<0.2) at each time point. Second, HR, fR, and NLCI increased from BSLN on Days 1–3; whereas CVC decreased on Days 2 and 3. In contrast, changes in BP and the relative low-(LF) and high-frequency (HF) of HRV were not significant. The coefficient of variation decreased from BSLN to Day 3, except for CVC. Interestingly, NLCI increased before fR in LPS-treated rats. Finally, we histologically confirmed lung injury, systemic inflammation via ELISA and the presence of the proinflammatory cytokine, IL-1β, with immunohistochemistry in the ponto-medullary respiratory nuclei. Discussion: Our findings support that NLCI reflects changes in the rat’s health induced by systemic injection of LPS and reflected in increases in HR and fR. CVC decreased over the course to the experiment. We conclude that NLCI reflected the increase in predictability of the ventilatory waveform and (together with our previous work) may reflect action of inflammatory cytokines on the network generating respiration. Frontiers Media S.A. 2023-07-31 /pmc/articles/PMC10423997/ /pubmed/37583625 http://dx.doi.org/10.3389/fnetp.2023.1038531 Text en Copyright © 2023 Campanaro, Nethery, Guo, Kaffashi, Loparo, Jacono, Dick and Hsieh. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Network Physiology Campanaro, Cara K. Nethery, David E. Guo, Fei Kaffashi, Farhad Loparo, Kenneth A. Jacono, Frank J. Dick, Thomas E. Hsieh, Yee-Hsee Dynamics of ventilatory pattern variability and Cardioventilatory Coupling during systemic inflammation in rats |
title | Dynamics of ventilatory pattern variability and Cardioventilatory Coupling during systemic inflammation in rats |
title_full | Dynamics of ventilatory pattern variability and Cardioventilatory Coupling during systemic inflammation in rats |
title_fullStr | Dynamics of ventilatory pattern variability and Cardioventilatory Coupling during systemic inflammation in rats |
title_full_unstemmed | Dynamics of ventilatory pattern variability and Cardioventilatory Coupling during systemic inflammation in rats |
title_short | Dynamics of ventilatory pattern variability and Cardioventilatory Coupling during systemic inflammation in rats |
title_sort | dynamics of ventilatory pattern variability and cardioventilatory coupling during systemic inflammation in rats |
topic | Network Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10423997/ https://www.ncbi.nlm.nih.gov/pubmed/37583625 http://dx.doi.org/10.3389/fnetp.2023.1038531 |
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