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Journal of Shanghai Jiaotong University(Science) >

2021 , Vol. 26 >Issue 1: 47 - 54

DOI: https://doi.org/10.1007/s12204-021-2259-7

Medicine-Engineering Interdisciplinary Research

Blood Pressure Change in Intrafascicular Vagal Activities

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  • (1. School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; 2. Shanghai Institute of
    Hypertension, Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China;
    3. Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou 215123, Jiangsu, China)

Online published: 2021-01-19

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Abstract

Baroreflex plays a significant role in modulating blood pressure for the human body. It is known that activation of the vagal nerve related to baroreflex can lead to reductions of blood pressure. However, how the vagal activities quantitatively relate with blood pressure can hardly be achieved. Here fine carbon nanotube yarn (CNTy) electrodes were adopted for recording intrafascicular vagal activities, synchronized with measurement of arterial blood pressure in a rat. Together with a novel algorithm, the results preliminarily quantified that there were six clusters of neural spikes within recorded vagal activities, and the number of individual vagal spikes correspondingly varied with blood pressure. Especially for Cluster 2, the neural activations decreased with arterial blood pressure increasing. This study can shed lights on the quantified neural mechanism underlying the control of vagal activities on blood pressure, and guide the vagal-nerve neuromodulation for treating hypertension.

Key words： vagal nerve; hypertension; baroreflex; signal processing; neuromodulation; carbon nanotube yarn

Cite this article

GUO Jinyao (郭金尧), LI Runhuan (李润桓), WANG Jiaojiao (王娇娇), ARRANZ Javier, LI Yiran (李怡然), CHAI Xinyu (柴新禹), WANG Jiguang (王继光), SUI Xiaohong (隋晓红) . Blood Pressure Change in Intrafascicular Vagal Activities[J]. Journal of Shanghai Jiaotong University(Science), 2021 , 26(1) : 47 -54 . DOI: 10.1007/s12204-021-2259-7

References

[1] World Health Organization. Noncommunicablediseases [EB/OL]. (2018-06-01) [2020-04-22].https:// www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases.
[2] ZHANG Y T. Editorial health engineering: Convergencetransforming reactive medicine to proactivehealthcare [J]. IEEE Reviews in Biomedical Engineering,2018, 11: 1.
[3] LIM S S, VOS T, FLAXMAN A D, et al. A comparativerisk assessment of burden of disease and injuryattributable to 67 risk factors and risk factor clustersin 21 regions, 1990-2010: A systematic analysis for theglobal burden of disease study 2010 [J]. The Lancet,2012, 380(9859): 2224-2260.
[4] SUN N L, HUO Y, WANG J G, et al. Chinese exports’consensus on the diagnosis and treatment of resistanthypertension [J]. Chinese Journal of Hypertension,2013, 21(4): 321-326 (in Chinese).
[5] SCHEFFERS I J, KROON A A, TORDOIR J H, et al.Rheos baroreflex hypertension therapy system to treatresistant hypertension [J]. Expert Review of MedicalDevices, 2008, 5(1): 33-39.
[6] BISOGNANO J D, BAKRIS G, NADIM M K, etal. Baroreflex activation therapy lowers blood pressurein patients with resistant hypertension: Resultsfrom the double-blind, randomized, placebo-controlledrheos pivotal trial [J]. Journal of the American Collegeof Cardiology, 2011, 58(7): 765-773.
[7] GIERTHMUEHLEN M, PLACHTA D T. Effect of selectivevagal nerve stimulation on blood pressure, heartrate and respiratory rate in rats under metoprolol medication[J]. Hypertension Research, 2016, 39(2): 79-87.
[8] North American Neuromodulation Society. About neuromodulation[EB/OL]. [2020-04-22]. https://neuromodulation.org/Default.aspx?TabID=442.
[9] KOUGIAS P, WEAKLEY S M, YAO Q, et al. Arterialbaroreceptors in the management of systemichypertension [J]. Medical Science Monitor: InternationalMedical Journal of Experimental and ClinicalResearch, 2010, 16(1): RA1-RA8.
[10] PLACHTA D T T, GIERTHMUEHLEN M, COTA O, et al. Blood pressure control with selective vagalnerve stimulation and minimal side effects [J]. Journalof Neural Engineering, 2014, 11(3): 036011.
[11] SEVCENCU C, NIELSEN T N, STRUIJK J J. Anintraneural electrode for bioelectronic medicines fortreatment of hypertension [J]. Neuromodulation: Technologyat the Neural Interface, 2018, 21(8): 777-786.
[12] DING F. Neurobiology [M]. 3rd ed. Beijing, China:Science Press, 2016: 95-95 (in Chinese).
[13] VITALE F, SUMMERSON S R, AAZHANG B, et al.Neural stimulation and recording with bidirectional,soft carbon nanotube fiber microelectrodes [J]. ACSNano, 2015, 9(4): 4465-4474.
[14] ZHU F Y, ZHU J R, ZHANG X, et al. Flexural characterizationof carbon nanotube (CNT) yarn neuralelectrodes [J]. Materials Research Express, 2019, 6(4):045402.
[15] SU J Y, ZHANG X, LI M N, et al. Insulation of carbonnanotube yarn electrodes for intrafascicular neuralstimulation and recording [C]//2019 9th InternationalIEEE/EMBS Conference on Neural Engineering(NER). Piscataway, NJ, USA: IEEE, 2019: 815-818.
[16] YU X, SU J Y, GUO J Y, et al. Spatiotemporal characteristicsof neural activity in tibial nerves with carbonnanotube yarn electrodes [J]. Journal of NeuroscienceMethods, 2019, 328: 108450.
[17] MCCALLUM G A, SUI X, QIU C, et al. Chronic interfacingwith the autonomic nervous system using carbonnanotube (CNT) yarn electrodes [J]. Scientific Reports,2017, 7(1): 11723.
[18] ZANOS T P, SILVERMAN H A, LEVY T, et al. Identificationof cytokine-specific sensory neural signals bydecoding murine vagus nerve activity [J]. Proceedingsof the National Academy of Sciences of the UnitedStates of America, 2018, 115(21): E4843-E4852.
[19] ARRANZ J, GUO J Y, YU X, et al. Intrafascicularvagal activity recording and analysis based on carbonnanotube yarn electrodes [J]. Journal of Shanghai JiaoTong University (Science), 2020, 25(4): 447-452.
[20] DAI H, HAN Z K, LI W Q, et al. A method to producesimple and practical rat carotid arterial catheterand an improvement on the intubation catheter model[J]. Journal of China Medical University, 2009, 38(10):798-799 (in Chinese).
[21] NASON G P, SILVERMAN B W. The stationarywavelet transform and some statistical applications[M]//Wavelets and statistics. New York, NY, USA:Springer, 1995: 281-299.
[22] LIEB F, STARK H G, THIELEMANN C. A stationarywavelet transform and a time-frequency based spikedetection algorithm for extracellular recorded data [J].Journal of Neural Engineering, 2017, 14(3): 036013.
[23] VAN DER MAATEN L, HINTON G. Visualizing datausing t-SNE [J]. Journal of Machine Learning Research,2008, 9: 2579-2625.
[24] ESTER M, KRIEGEL H P, SANDER J, et al. Adensity-based algorithm for discovering clusters inlarge spatial databases with noise [EB/OL]. (1996-12-16) [2020-04-22]. https://www.aaai.org/Papers/KDD/1996/KDD96-037.pdf?source=post page.
[25] CHO S H, LU H M, CAULLER L, et al. BiocompatibleSU-8-based microprobes for recording neural spike signalsfrom regenerated peripheral nerve fibers [J]. IEEESensors Journal, 2008, 8(11): 1830-1836.

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