Electrophysiological Effects Of Kappa-Opioid Analgesic, RU-1205, Using Machine Learning Methods

κ-opioid receptor
DOI: 10.1101/2024.02.11.579812 Publication Date: 2024-02-12T20:10:15Z
ABSTRACT
This study focuses on RU-1205, a new kappa-opioid agonist exhibiting analgesic effect without causing dysphoric or aversive reactions. It is assumed that the absence of effects can be attributed to functional selectivity it might due an additional mechanism action involves blocking p38 mitogen-activated protein kinase (MAPK). The aim this was experimental identification mechanisms RU-1205 associated with inhibition MAPK and at receptors. Materials methods Rats weighing 260-280 g were implanted chronic cortical deep electrodes. LFP activity recorded after intracerebroventricular administration well-studied reference substances: selective U-50488 dose 100 μg; blocker SB203580 1 investigational compound 350 μg. weighted phase lag index (WPLI) calculated. Subsequently, machine learning techniques employed reduce dimensionality extract connectivity features using principal component analysis method. Finally, signal classification conducted models based Gaussian processes. By applying patch-clamp technique in whole-cell configuration, spike pyramidal neurons basolateral amygdala studied. identified by their accommodation properties. After local perfusion test compounds, 3 dose-response curves obtained for: (1) concentrations ranging from 0.001 10 μM; (2) combinations (0.001–10 μM) (10 μM); (3) (0.01–10 (100 μM). Results developed able classify as «non-inhibitor» probability 0.89. results confirmed patch clamp experiments acute brain slices, where demonstrated statistically significantly increases (p <0.05) interacts U-50488, suppressing its neurons. Conclusions findings suggest displays properties consistent kappa opioid receptor does not have significant p38. demonstrates possibility integrating electrophysiological measurements advanced data for understanding neuronal drug underscores potential further research area.
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