Abstract: FR-PO379
A Novel Method for the Analysis of Renal Sympathetic Nerve Activity (RSNA) from Multi-Fiber Nerve Recordings
Session Information
- Hypertension and CVD: Basic
November 03, 2023 | Location: Exhibit Hall, Pennsylvania Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Hypertension and CVD
- 1601 Hypertension and CVD: Basic
Authors
- Rodionova, Kristina, Friedrich-Alexander-Universitat Erlangen-Nurnberg, Erlangen, Bayern, Germany
- Veelken, Roland, Friedrich-Alexander-Universitat Erlangen-Nurnberg, Erlangen, Bayern, Germany
- Cordasic, Nada, Friedrich-Alexander-Universitat Erlangen-Nurnberg, Erlangen, Bayern, Germany
- Hilgers, Karl F., Friedrich-Alexander-Universitat Erlangen-Nurnberg, Erlangen, Bayern, Germany
- Schiffer, Mario, Friedrich-Alexander-Universitat Erlangen-Nurnberg, Erlangen, Bayern, Germany
- Amann, Kerstin U., Friedrich-Alexander-Universitat Erlangen-Nurnberg, Erlangen, Bayern, Germany
- Ditting, Tilmann, Friedrich-Alexander-Universitat Erlangen-Nurnberg, Erlangen, Bayern, Germany
Background
Measurement of RSNA via bipolar electrodes from multi-fiber preparations in various species has been used for decades in the context of autonomic regulation research. Traditionally, raw neurograms are usually integrated over short time intervals and this approach works perfectly for the analysis of dynamic RSNA changes due to acute intervention. However, comparability of baseline activities between groups is limited. We present a novel analysis method, based on the raw neurogram sampled at rate of 25 kHz.
Methods
For RSNA-burst analysis a software based programmable algorithm was used. Continuous activities longer than three single spikes (i.e., >8ms) were defined as bursts, followed by silent periods with some single spikes. Approximately 10.000 bursts/rat were analyzed and burst amplitude, burst duration, burst area (i.e., duration integral), as well as the burst frequencies were analyzed.
Results
In rats with myocardial infarction (n=11) we found no difference in integrated baseline RSNA as compared to controls ((n=10). However, the new method revealed higher higher burst rate per cardiac cycle [CC] (2.65 ± 0.39 vs. 1.61 ± 0.38 bursts/CC; P<0.001) and burst frequency (15.09 ± 2.42 vs. 8.52 ±1.54 Hz; P<0.001) compared to healthy controls, indicating increased RSNA.
Conclusion
Our new method of RSNA baseline analysis was able to detect subtle differences between groups of animals that could not be detected by the traditional method of integrated RSNA analysis. Furthermore, this method has the potential to give further insights into RNSA patterns and synchronization to afferent regulatory input form the kidney itself or other organs.