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Search for author "Mark R. Boyett"

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  • You have accessRestricted access
    Abstract 430: Circadian Control of Heart Rate
    Alicia D’souza, Sven Wegner, Anne Berit Johnsen, Eleanor Gill, Charlotte Cox, Halina Dobrzynski, Ulrik Wisløff, George Hart, Hugh D Piggins and Mark R Boyett
    Circulation Research. 2015;117:A430
  • You have accessRestricted access
    Letter by Monfredi et al Regarding Article, “Physical Activity and Heart Rate Variability in Older Adults: The Cardiovascular Health Study”
    Oliver Monfredi, Henggui Zhang and Mark R. Boyett
    Circulation. 2015;131:e348, originally published February 17, 2015
    https://doi.org/10.1161/CIRCULATIONAHA.114.011515
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  • You have accessRestricted access
    Biophysical Characterization of the Underappreciated and Important Relationship Between Heart Rate Variability and Heart RateNovelty and Significance
    Oliver Monfredi, Alexey E. Lyashkov, Anne-Berit Johnsen, Shin Inada, Heiko Schneider, Ruoxi Wang, Mahesh Nirmalan, Ulrik Wisloff, Victor A. Maltsev, Edward G. Lakatta, Henggui Zhang and Mark R. Boyett
    Hypertension. 2014;64:1334-1343, originally published September 15, 2014
    https://doi.org/10.1161/HYPERTENSIONAHA.114.03782
    Download PDF
  • You have access
    Biophysical Characterization of the Underappreciated and Important Relationship Between Heart Rate Variability and Heart RateNovelty and Significance
    Oliver Monfredi, Alexey E. Lyashkov, Anne-Berit Johnsen, Shin Inada, Heiko Schneider, Ruoxi Wang, Mahesh Nirmalan, Ulrik Wisloff, Victor A. Maltsev, Edward G. Lakatta, Henggui Zhang, Mark R. Boyett
    Hypertension December 2014, 64 (6) 1334-1343; DOI: https://doi.org/10.1161/HYPERTENSIONAHA.114.03782
    Figure 1.
    Figure 1.
    Differences in heart rate variability (HRV) among different cardiac preparations (baseline conditions)....
    Show More
    Differences in heart rate variability (HRV) among different cardiac preparations (baseline conditions). A to E, Tachograms (150-s stationary epochs) from (A) conscious human (n=11), (B) Langendorff-perfused rabbit heart (n=58), (C) rabbit sinoatrial node cell (SANC; n=67), (D) Langendorff-perfused rat heart (n=8), (E) conscious rat (n=11). Individual experiments are plotted in unique colours. F to H, Summary of baseline differences in cycle length (CL) and HRV among cardiac preparations. Mean (+SEM) CL (F), SD of normal beat to normal beat intervals (SDNN; G), and root mean square of successive differences (RMSSD) (H) for different preparations. Asterisk and letters atop bars demonstrate statistically significant differences from other lettered bars (P<0.05; 1-way ANOVA).
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  • You have access
    Biophysical Characterization of the Underappreciated and Important Relationship Between Heart Rate Variability and Heart RateNovelty and Significance
    Oliver Monfredi, Alexey E. Lyashkov, Anne-Berit Johnsen, Shin Inada, Heiko Schneider, Ruoxi Wang, Mahesh Nirmalan, Ulrik Wisloff, Victor A. Maltsev, Edward G. Lakatta, Henggui Zhang, Mark R. Boyett
    Hypertension December 2014, 64 (6) 1334-1343; DOI: https://doi.org/10.1161/HYPERTENSIONAHA.114.03782
    Figure 2.
    Figure 2.
    Effect of β-agonists on heart rate variability (HRV) in different cardiac preparations. A t...
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    Effect of β-agonists on heart rate variability (HRV) in different cardiac preparations. A to D, Tachograms demonstrating the effect of β-agonists on HRV. A, Before and after dobutamine in conscious humans. B, Data before and after 100 nmol/L isoprenaline in rabbit sinoatrial node cell (SANC). C, Data before and after 100 nmol/L isoprenaline in Langendorff-perfused rabbit hearts. D, Data before and after 100 nmol/L isoprenaline in Langendorff-perfused rat hearts. Baseline data are shown in red, and data in presence of β-adrenergic agonist are shown in green. E to G, summary of the effect of β-adrenergic agonists on HRV. Mean (+SEM) CL (E), SD of normal beat to normal beat intervals (SDNN; F), and root mean square of successive differences (RMSSD) (G) under baseline conditions (=B; red bars) and with β-adrenergic agonist (=C; green bars) for the different preparations. Asterisk and bar indicate statistically different (P<0.05; 1-way ANOVA). Sword and bar indicate P=0.1>P>0.05.
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  • You have access
    Biophysical Characterization of the Underappreciated and Important Relationship Between Heart Rate Variability and Heart RateNovelty and Significance
    Oliver Monfredi, Alexey E. Lyashkov, Anne-Berit Johnsen, Shin Inada, Heiko Schneider, Ruoxi Wang, Mahesh Nirmalan, Ulrik Wisloff, Victor A. Maltsev, Edward G. Lakatta, Henggui Zhang, Mark R. Boyett
    Hypertension December 2014, 64 (6) 1334-1343; DOI: https://doi.org/10.1161/HYPERTENSIONAHA.114.03782
    Figure 3.
    Figure 3.
    Relationship between heart rate variability (HRV; SD of normal beat to normal beat intervals [SDNN]) and hea...
    Show More
    Relationship between heart rate variability (HRV; SD of normal beat to normal beat intervals [SDNN]) and heart rate: comparison of theory and experiment. A, Relationship between SDNN and heart rate. Data from experiments undertaken in this article and elsewhere, and our mathematical models are plotted. Basic key under A; for detailed key, see online-only Data Supplement. B, Relationship between SDNN and heart rate (heart rate range, 40–240 bpm only). C, Relationship between logn(SDNN) and heart rate (same data as A). Black line shows that for every 10 bpm increase in heart rate, logn(SDNN) decreases by 0.17 ms.
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  • You have access
    Biophysical Characterization of the Underappreciated and Important Relationship Between Heart Rate Variability and Heart RateNovelty and Significance
    Oliver Monfredi, Alexey E. Lyashkov, Anne-Berit Johnsen, Shin Inada, Heiko Schneider, Ruoxi Wang, Mahesh Nirmalan, Ulrik Wisloff, Victor A. Maltsev, Edward G. Lakatta, Henggui Zhang, Mark R. Boyett
    Hypertension December 2014, 64 (6) 1334-1343; DOI: https://doi.org/10.1161/HYPERTENSIONAHA.114.03782
    Figure 4.
    Figure 4.
    Relationship between heart rate variability (HRV) and heart rate predicted by a biophysically detailed model...
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    Relationship between heart rate variability (HRV) and heart rate predicted by a biophysically detailed model. Computed action potentials from a sinoatrial node cell (SANC) model with (green) and without (red) a maximum 20-pA perturbing current (Iper) at fast (top, eg, Ai) to slow (bottom, eg, Ci) rates, and corresponding tachograms (Aii–Cii). Rate was varied by altering ACh-activated K+ current (IK,ACh). D, Relationship between SD of normal beat to normal beat intervals (SDNN) and heart rate in this model.
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  • You have access
    Biophysical Characterization of the Underappreciated and Important Relationship Between Heart Rate Variability and Heart RateNovelty and Significance
    Oliver Monfredi, Alexey E. Lyashkov, Anne-Berit Johnsen, Shin Inada, Heiko Schneider, Ruoxi Wang, Mahesh Nirmalan, Ulrik Wisloff, Victor A. Maltsev, Edward G. Lakatta, Henggui Zhang, Mark R. Boyett
    Hypertension December 2014, 64 (6) 1334-1343; DOI: https://doi.org/10.1161/HYPERTENSIONAHA.114.03782
    Figure 5.
    Figure 5.
    Application of a correcting factor facilitates clarification of whether changes in heart rate variability (H...
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    Application of a correcting factor facilitates clarification of whether changes in heart rate variability (HRV) are attributable to heart rate differences alone. Analysis of baseline differences in HRV among different preparations (A); analysis of changes in HRV after administration of β-agonists to different preparations (B–E). SD of normal beat to normal beat intervals (SDNN) is plotted against heart rate. Predicted effect of heart rate on SDNN is plotted (green lines) using calculated correcting factor from Figure 3C. Conscious human data (A) or baseline data (B–E) are arbitrarily used as starting point from which to calculate the effect of heart rate on SDNN.
    Show Less
  • You have accessRestricted access
    Biophysical Characterization of the Underappreciated and Important Relationship Between Heart Rate Variability and Heart RateNovelty and Significance
    Oliver Monfredi, Alexey E. Lyashkov, Anne-Berit Johnsen, Shin Inada, Heiko Schneider, Ruoxi Wang, Mahesh Nirmalan, Ulrik Wisloff, Victor A. Maltsev, Edward G. Lakatta, Henggui Zhang and Mark R. Boyett
    Hypertension. 2014;64:1334-1343, originally published September 15, 2014
    https://doi.org/10.1161/HYPERTENSIONAHA.114.03782
    Download PDF
  • You have access
    Biophysical Characterization of the Underappreciated and Important Relationship Between Heart Rate Variability and Heart RateNovelty and Significance
    Oliver Monfredi, Alexey E. Lyashkov, Anne-Berit Johnsen, Shin Inada, Heiko Schneider, Ruoxi Wang, Mahesh Nirmalan, Ulrik Wisloff, Victor A. Maltsev, Edward G. Lakatta, Henggui Zhang, Mark R. Boyett
    Hypertension December 2014, 64 (6) 1334-1343; DOI: https://doi.org/10.1161/HYPERTENSIONAHA.114.03782
    Figure 1.
    Figure 1.
    Differences in heart rate variability (HRV) among different cardiac preparations (baseline conditions)....
    Show More
    Differences in heart rate variability (HRV) among different cardiac preparations (baseline conditions). A to E, Tachograms (150-s stationary epochs) from (A) conscious human (n=11), (B) Langendorff-perfused rabbit heart (n=58), (C) rabbit sinoatrial node cell (SANC; n=67), (D) Langendorff-perfused rat heart (n=8), (E) conscious rat (n=11). Individual experiments are plotted in unique colours. F to H, Summary of baseline differences in cycle length (CL) and HRV among cardiac preparations. Mean (+SEM) CL (F), SD of normal beat to normal beat intervals (SDNN; G), and root mean square of successive differences (RMSSD) (H) for different preparations. Asterisk and letters atop bars demonstrate statistically significant differences from other lettered bars (P<0.05; 1-way ANOVA).
    Show Less

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  • Structure 27
  • Volume 128, Issue 22 Supplement; November 26, 2013 / Abstracts From the American Heart Association 2013 Scientific Sessions and Resuscitation Science Symposium 4
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  • Ablation/ICD/surgery 32
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  • Electrophysiology 68
  • Gene expression 42
  • Heart Failure 30
  • Heart failure - basic studies 22
  • Hypertrophy 9
  • Imaging 32
  • Ion Channels/Membrane Transport 11
  • Ion channels/membrane transport 96
  • Ischemic biology - basic studies 17
  • Myocardial Infarction 10
  • Myogenesis 1
  • Other heart failure 22
  • Other myocardial biology 63
  • Pacemaker 21
  • Physiological and pathological control of gene expression 75
  • Pulmonary Hypertension 11
  • Quantitative modeling 56
  • Remodeling 10
  • Structure 84
  • Translational Studies 9
  • Volume 128, Issue 22 Supplement; November 26, 2013 / Abstracts From the American Heart Association 2013 Scientific Sessions and Resuscitation Science Symposium 4
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  • Articles 57
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  • HWTABLE 1
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