Left atrial mechanics and aortic stiffness following high intensity interval training: a randomised controlled study

Purpose: High intensity interval training (HIIT) has been shown to improve important health parameters, including aerobic capacity, blood pressure, cardiac autonomic modulation and left ventricular (LV) mechanics. However, adaptations in left atrial (LA) mechanics and aortic stiffness remain unclear. Methods: Forty-one physically inactive males and females were recruited. Participants were randomised to either a 4-week HIIT intervention (n=21) or 4-week control period (n=20). The HIIT protocol consisted of 3x30-second maximal cycle ergometer sprints with a resistance of 7.5% body weight, interspersed with 2-minutes of active unloaded recovery, 3 times per week. Speckle tracking imaging of the LA and M-Mode tracing of the aorta was performed pre and post HIIT and control period. Results: Following HIIT, there was significant improvement in LA mechanics, including LA reservoir (13.9±13.4%, p=0.033), LA conduit (8.9±11.2%, p=0.023) and LA contractile (5±4.5%, p=0.044) mechanics compared to the control condition. In addition, aortic distensibility (2.1±2.7cm2dyn-1103, p=0.031) and aortic stiffness index (-2.6±4.6, p=0.041) were improved compared to the control condition. In stepwise linear regression analysis, aortic distensibility change was significantly associated with LA stiffness change R2 of 0.613 (p=0.002). Conclusion: A short-term programme of HIIT was associated with a significant improvement in LA mechanics and aortic stiffness. These adaptations may have important health implications and contribute to the improved LV diastolic and systolic mechanics, aerobic capacity and blood pressure previously documented following HIIT

Modeling the differentiation of A- and C-type baroreceptor firing patterns

The baroreceptor neurons serve as the primary transducers of blood pressure for the autonomic nervous system and are thus critical in enabling the body to respond effectively to changes in blood pressure. These neurons can be separated into two types (A and C) based on the myelination of their axons and their distinct firing patterns elicited in response to specific pressure stimuli. This study has developed a comprehensive model of the afferent baroreceptor discharge built on physiological knowledge of arterial wall mechanics, firing rate responses to controlled pressure stimuli, and ion channel dynamics within the baroreceptor neurons. With this model, we were able to predict firing rates observed in previously published experiments in both A- and C-type neurons. These results were obtained by adjusting model parameters determining the maximal ion-channel conductances. The observed variation in the model parameters are hypothesized to correspond to physiological differences between A- and C-type neurons. In agreement with published experimental observations, our simulations suggest that a twofold lower potassium conductance in C-type neurons is responsible for the observed sustained basal firing, whereas a tenfold higher mechanosensitive conductance is responsible for the greater firing rate observed in A-type neurons. A better understanding of the difference between the two neuron types can potentially be used to gain more insight into the underlying pathophysiology facilitating development of targeted interventions improving baroreflex function in diseased individuals, e.g. in patients with autonomic failure, a syndrome that is difficult to diagnose in terms of its pathophysiology.Comment: Keywords: Baroreflex model, mechanosensitivity, A- and C-type afferent baroreceptors, biophysical model, computational mode

Measurement of aortic stiffness by laser doppler vibrometry : the cardis study

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