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The anterior nucleus of the paraventricular thalamus (aPVT) integrates various synaptic inputs and conveys information to the downstream brain regions for arousal and pain regulation. Recent studies have indicated that the PVT plays a crucial role in the regulation of chronic pain, but the plasticity mechanism of neuronal excitability and synaptic inputs for aPVT neurons in neuropathic pain remains unclear. Here, we report that spinal nerve ligation (SNL) significantly increased the neuronal excitability and reset the excitatory/inhibitory (E/I) synaptic inputs ratio of aPVT neurons in mice. SNL significantly increased the membrane input resistance, firing frequency, and the half-width of action potential. Additionally, SNL enlarged the area of afterdepolarization and prolonged the rebound low-threshold spike following a hyperpolarized current injection. Further results indicate that an inwardly rectifying current density was decreased in SNL animals. SNL also decreased the amplitude, but not the frequency of spontaneous excitatory postsynaptic currents (sEPSCs), nor the amplitude or frequency of spontaneous inhibitory postsynaptic currents (sIPSCs) of aPVT neurons. Moreover, SNL disrupted the E/I synaptic ratio, caused a decrease in weighted tau and half-width of averaged sIPSCs, but did not change these physiological properties of averaged sEPSCs. Finally, pharmacological activation of the GABAA receptor at aPVT could effective relieve SNL-induced mechanical allodynia in mice. These results reveal the plasticity of intrinsic neuronal excitability and E/I synaptic balance in the aPVT neurons after nerve injury and it may play an important role in the development of pain sensitization.
Pubmed ID: 35850188 RIS Download
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THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.
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