Feed Forward modeling: An efficient approach for mathematical modeling of the force frequency relationship in the rabbit isolated ventricular myocyte.

IF 1.3 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Biomedical Physics & Engineering Express Pub Date : 2024-09-10 DOI:10.1088/2057-1976/ad78e3
Robson Rodrigues da Silva,Gabriel Marcos de Sousa Motta,Matheus Leonardo Alves de Camargo,Daniel Gustavo Goroso,José Luis Puglisi
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This study addresses the Force - Frequency relationship, a fundamental characteristic of cardiac muscle influenced by β1-adrenergic stimulation. This relationship reveals that heart rate (HR) changes at the sinoatrial node lead to alterations in ventricular cell contractility, increasing the force and decreasing relaxation time for higher beat rates. Traditional models lacking this relationship offer an incomplete physiological depiction, impacting the interpretation of in silico experiment results. To improve this, we propose a new mathematical model for ventricular myocytes, named \"Feed Forward Modeling\" (FFM).
Methods:
FFM adjusts model parameters like channel conductance and Ca2+pump affinity according to stimulation frequency, in contrast to fixed parameter values. An empirical sigmoid curve guided the adaptation of each parameter, integrated into a rabbit ventricular cell electromechanical model. Model validation was achieved by comparing simulated data with experimental current-voltage (I-V) curves for L-type Calcium and slow Potassium currents.
Results:
FFM-enhanced simulations align more closely with physiological behaviors, accurately reflecting inotropic and lusitropic responses. For instance, action potential duration at 90% repolarization (APD90) decreased from 206 ms at 1 Hz to 173 ms at 4 Hz using FFM, contrary to the conventional model, where APD90 increased, limiting high-frequency heartbeats. Peak force also showed an increase with FFM, from 8.5 mN/mm2at 1 Hz to 11.9 mN/mm2at 4 Hz, while it barely changed without FFM. Relaxation time at 50% of maximum force (t50) similarly improved, dropping from 114 ms at 1 Hz to 75.9 ms at 4 Hz with FFM, a change not observed without the model.
Conclusion:
The FFM approach offers computational efficiency, bypassing the need to model all beta-adrenergic pathways, thus facilitating large-scale simulations. The study recommends that frequency change experiments include fractional dosing of isoproterenol to better replicate heart conditions in vivo.&#xD.","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":"82 1","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biomedical Physics & Engineering Express","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1088/2057-1976/ad78e3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
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Abstract

This study addresses the Force - Frequency relationship, a fundamental characteristic of cardiac muscle influenced by β1-adrenergic stimulation. This relationship reveals that heart rate (HR) changes at the sinoatrial node lead to alterations in ventricular cell contractility, increasing the force and decreasing relaxation time for higher beat rates. Traditional models lacking this relationship offer an incomplete physiological depiction, impacting the interpretation of in silico experiment results. To improve this, we propose a new mathematical model for ventricular myocytes, named "Feed Forward Modeling" (FFM). Methods: FFM adjusts model parameters like channel conductance and Ca2+pump affinity according to stimulation frequency, in contrast to fixed parameter values. An empirical sigmoid curve guided the adaptation of each parameter, integrated into a rabbit ventricular cell electromechanical model. Model validation was achieved by comparing simulated data with experimental current-voltage (I-V) curves for L-type Calcium and slow Potassium currents. Results: FFM-enhanced simulations align more closely with physiological behaviors, accurately reflecting inotropic and lusitropic responses. For instance, action potential duration at 90% repolarization (APD90) decreased from 206 ms at 1 Hz to 173 ms at 4 Hz using FFM, contrary to the conventional model, where APD90 increased, limiting high-frequency heartbeats. Peak force also showed an increase with FFM, from 8.5 mN/mm2at 1 Hz to 11.9 mN/mm2at 4 Hz, while it barely changed without FFM. Relaxation time at 50% of maximum force (t50) similarly improved, dropping from 114 ms at 1 Hz to 75.9 ms at 4 Hz with FFM, a change not observed without the model. Conclusion: The FFM approach offers computational efficiency, bypassing the need to model all beta-adrenergic pathways, thus facilitating large-scale simulations. The study recommends that frequency change experiments include fractional dosing of isoproterenol to better replicate heart conditions in vivo. .
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前馈建模:兔离体心室肌细胞力频关系数学建模的有效方法。
本研究探讨了力-频率关系,这是心肌受β1-肾上腺素能刺激影响的基本特征。这种关系揭示了心房结的心率(HR)变化会导致心室细胞收缩力的改变,在搏动率较高时,心室细胞收缩力增加,松弛时间缩短。缺乏这种关系的传统模型提供了不完整的生理描述,影响了对硅学实验结果的解释。方法: FFM 根据刺激频率调整通道电导和 Ca2+ 泵亲和力等模型参数,而不是固定参数值。每种参数的调整都由一条经验乙型曲线引导,并与兔心室细胞机电模型相结合。通过将模拟数据与 L 型钙电流和慢钾电流的实验电流-电压(I-V)曲线进行比较,对模型进行了验证。例如,使用 FFM 时,90% 复极化时的动作电位持续时间(APD90)从 1 Hz 时的 206 毫秒降至 4 Hz 时的 173 毫秒,而在传统模型中,APD90 会增加,从而限制高频率心跳。峰值力也随着 FFM 的使用而增加,从 1 赫兹时的 8.5 毫牛顿/平方毫米增加到 4 赫兹时的 11.9 毫牛顿/平方毫米,而不使用 FFM 时几乎没有变化。50%最大力时的松弛时间(t50)也同样有所改善,FFM 使其从 1 Hz 时的 114 毫秒下降到 4 Hz 时的 75.9 毫秒,而没有 FFM 模型时则观察不到这一变化。研究建议频率变化实验包括异丙肾上腺素的部分剂量,以更好地复制体内心脏状况。
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来源期刊
Biomedical Physics & Engineering Express
Biomedical Physics & Engineering Express RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
2.80
自引率
0.00%
发文量
153
期刊介绍: BPEX is an inclusive, international, multidisciplinary journal devoted to publishing new research on any application of physics and/or engineering in medicine and/or biology. Characterized by a broad geographical coverage and a fast-track peer-review process, relevant topics include all aspects of biophysics, medical physics and biomedical engineering. Papers that are almost entirely clinical or biological in their focus are not suitable. The journal has an emphasis on publishing interdisciplinary work and bringing research fields together, encompassing experimental, theoretical and computational work.
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