Capsaicin- resistant arterial baroreceptors

BACKGROUND: Aortic baroreceptors (BRs) comprise a class of cranial afferents arising from major arteries closest to the heart whose axons form the aortic depressor nerve. BRs are mechanoreceptors that are largely devoted to cardiovascular autonomic reflexes. Such cranial afferents have either lightly myelinated (A-type) or non-myelinated (C-type) axons and share remarkable cellular similarities to spinal primary afferent neurons. Our goal was to test whether vanilloid receptor (TRPV1) agonists, capsaicin (CAP) and resiniferatoxin (RTX), altered the pressure-discharge properties of peripheral aortic BRs. RESULTS: Periaxonal application of 1 μM CAP decreased the amplitude of the C-wave in the compound action potential conducting at <1 m/sec along the aortic depressor nerve. 10 μM CAP eliminated the C-wave while leaving intact the A-wave conducting in the A-δ range (<12 m/sec). These whole nerve results suggest that TRPV1 receptors are expressed along the axons of C- but not A-conducting BR axons. In an aortic arch – aortic nerve preparation, intralumenal perfusion with 1 μM CAP had no effect on the pressure-discharge relations of regularly discharging, single fiber BRs (A-type) – including the pressure threshold, sensitivity, frequency at threshold, or maximum discharge frequency (n = 8, p > 0.50) but completely inhibited discharge of an irregularly discharging BR (C-type). CAP at high concentrations (10–100 μM) depressed BR sensitivity in regularly discharging BRs, an effect attributed to non-specific actions. RTX (≤ 10 μM) did not affect the discharge properties of regularly discharging BRs (n = 7, p > 0.18). A CAP-sensitive BR had significantly lower discharge regularity expressed as the coefficient of variation than the CAP-resistant fibers (p < 0.002). CONCLUSION: We conclude that functional TRPV1 channels are present in C-type but not A-type (A-δ) myelinated aortic arch BRs. CAP has nonspecific inhibitory actions that are unlikely to be related to TRV1 binding since such effects were absent with the highly specific TRPV1 agonist RTX. Thus, CAP must be used with caution at very high concentrations

Modeling the Afferent Dynamics of the Baroreflex Control System

In this study we develop a modeling framework for predicting baroreceptor firing rate as a function of blood pressure. We test models within this framework both quantitatively and qualitatively using data from rats. The models describe three components: arterial wall deformation, stimulation of mechanoreceptors located in the BR nerve-endings, and modulation of the action potential frequency. The three sub-systems are modeled individually following well-established biological principles. The first submodel, predicting arterial wall deformation, uses blood pressure as an input and outputs circumferential strain. The mechanoreceptor stimulation model, uses circumferential strain as an input, predicting receptor deformation as an output. Finally, the neural model takes receptor deformation as an input predicting the BR firing rate as an output. Our results show that nonlinear dependence of firing rate on pressure can be accounted for by taking into account the nonlinear elastic properties of the artery wall. This was observed when testing the models using multiple experiments with a single set of parameters. We find that to model the response to a square pressure stimulus, giving rise to post-excitatory depression, it is necessary to include an integrate-and-fire model, which allows the firing rate to cease when the stimulus falls below a given threshold. We show that our modeling framework in combination with sensitivity analysis and parameter estimation can be used to test and compare models. Finally, we demonstrate that our preferred model can exhibit all known dynamics and that it is advantageous to combine qualitative and quantitative analysis methods

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