Utilização do análogo elétrico de membrana para classificação dos neurônios do gânglio cervical superior de ratos

• Ano de defesa: 2022
• Autor(a) principal: Freitas, Leonardo Félix
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Biblioteca da Universidade Federal do Ceará
• Palavras-chave em Português: Gânglio cervical superior; Canais iônicos
• Link de acesso: http://www.repositorio.ufc.br/handle/riufc/68066

The superior cervical ganglion (SCG) is a structure of the sympathetic autonomic nervous system, which contains the neurons that innervate the neck and face, but also provides sympathetic innervation to the heart and pineal gland. The membrane of these neu rons can be modeled by an electrical analogue, in which the ion channels are represented by conductances, the moving force of ions by batteries and the plasma membrane by a capacitor. The use of this membrane electrical analogue makes it possible to study the electrical properties of the neuronal membrane and assist in cell classification through the passive properties of membranes. The objective of this work was to investigate, through the use of the membrane electrical analogue, the passive electrical pro perties and their influence on the functioning of neurons in the superior cervical ganglion of rats. The data for this work come from the project submitted to the CEUA/UECE, which received approval under number 4695010/2016. Initially, a program was made i n C language that modeled the membrane of GCS neurons using the equations of a simple resistor -capacitor circuit. Then, the experimental data of current-voltage (IxV) of the neurons of the GCS were analyzed, and the electrophysiological parameters resting potential (Em), input resistance (Rin) and voltage decay time (τm) were entered into the program to obtaining simulated IxV curves and neuronal membrane data. With the experimental and simulated data from the IxV curves, the two signals were subtracted and the responses analyzed. In all, 8 animals were used, 77 cells were obtained for electrophysiological data, and the results are expressed as mean ± E.P.M, where the number in parentheses represents the number of neurons. For comparison between groups, the one-way ANOVA test followed by the Holm-Sidak post-test was used, and the groups showed statistical difference when the p -value for the occurrence of the null hypothesis was less than or equal to 0.05. On visual inspection of the IxV curves, some neurons showed voltage rectification when a hyperpolarizing pulse of 500 pA was applied. Thus, we initially classified neurons as non -rectified (SR) and depolarizing rectified (CRD). When we obtained the experimental and simulated IxV subtractions, we verified anot her neuronal group, which presented a negative deflection in the subtracted signal. Thus, we obtained three neuronal groups: SR, CRD and with hyperpolarizing rectification (CRH). Between the groups, there was no statistical difference in the parameters Em and Rin. There was a statistical difference (p < 0.05 followed by Holm -Sidak) in τm and the value for the SR, CRD and CRH group was 13.2 ± 1.0 (n = 50), 6.7 ± 0.8 ( n = 17) and 13.2 ± 0.8 ms (n = 10), respectively. In active parameters, rheobase showed no statistical difference between groups, but all action potential (AP) parameters showed statistical difference (p < 0.05, ANOVA followed by Holm -Sidak) between the SR and CRD groups. The PA amplitude of the SR, CRD and CRH groups was 76.4 ± 1.6 (n = 50), 67 .1 ± 3.8 (n = 17) and 80.2 ± 2.7 mV (n = 10 ) and there was a statistical difference between the groups. Likewise, the SR, CRD and CRH groups showed a statistical difference between themselves in the maximum ascending slope of the AP and their values were 78.8 ± 4.3 (n = 50), 58.6 ± 6.1 (n = 17 ) and 87.4 ± 8.2 V/s (n = 10), respectively. The use of the membrane electrical analogue allowed the classification of superior cervical ganglion neurons into groups with different electrophysiological properties. This approach can be used to improve the classification of GCS neurons in both physiological and pathological situations.