Long-Term Actions of Interleukin-1β on Delay and Tonic Firing Neurons in Rat Superficial Dorsal Horn and Their Relevance to Central Sensitization
Bibliographic record
Abstract
BACKGROUND: Cytokines such as interleukin 1beta (IL-1beta) have been implicated in the development of central sensitization that is characteristic of neuropathic pain. To examine its long-term effect on nociceptive processing, defined medium organotypic cultures of rat spinal cord were exposed to 100 pM IL-1beta for 6-8 d. Interleukin effects in the dorsal horn were examined by whole-cell patch-clamp recording and Ca(2+) imaging techniques. RESULTS: Examination of the cultures with confocal Fluo-4 AM imaging showed that IL-1beta increased the change in intracellular Ca(2+) produced by exposure to 35-50 mM K+. This is consistent with a modest increase in overall dorsal horn excitability. Despite this, IL-1beta did not have a direct effect on rheobase or resting membrane potential nor did it selectively destroy any specific neuronal population. All effects were instead confined to changes in synaptic transmission. A variety of pre- and postsynaptic actions of IL-1beta were seen in five different electrophysiologically-defined neuronal phenotypes. In putative excitatory 'delay' neurons, cytokine treatment increased the amplitude of spontaneous EPSC's (sEPSC) and decreased the frequency of spontaneous IPSC's (sIPSC). These effects would be expected to increase dorsal horn excitability and to facilitate the transfer of nociceptive information. However, other actions of IL-1beta included disinhibition of putative inhibitory 'tonic' neurons and an increase in the amplitude of sIPSC's in 'delay' neurons. CONCLUSION: Since spinal microglial activation peaks between 3 and 7 days after the initiation of chronic peripheral nerve injury and these cells release IL-1beta at this time, our findings define some of the neurophysiological mechanisms whereby nerve-injury induced release of IL-1beta may contribute to the central sensitization associated with chronic neuropathic pain.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".