IL-1β directly excites isolated rat supraoptic neurons via upregulation of the osmosensory cation current
Bibliographic record
Abstract
Previous studies have shown that IL-1beta can excite the magnocellular neurosecretory cells (MNCs) of the hypothalamus. However, it is not known whether IL-1beta can have direct IL-1 receptor type 1 (IL-1R1)-mediated effects on MNCs, and little is known about the cellular mechanisms by which IL-1beta influences electrical activity in these cells. Here, we used patch-clamp recordings to examine the effects of IL-1beta on acutely isolated rat MNCs. We found that IL-1beta directly excites MNCs in a dose-dependent manner and that this response can be blocked by an inhibitor of the IL-1R1. Voltage-clamp analysis of the current evoked by IL-1beta revealed a linear current-voltage relationship between -90 and -20 mV, and a reversal potential near -35 mV. This value was not affected by reducing the concentration of chloride ions in the external solution, indicating the involvement of a nonselective cation conductance. The effects of IL-1beta were inhibited by Na-salicylate, an inhibitor of cyclooxygenase. Moreover, the effects of IL-1beta were mimicked and occluded by PGE2, and were inhibited by AH-23848, an antagonist of the PGE2 type 4 (i.e., EP4) receptor. The current evoked by IL-1beta was also abolished by 100 microM gadolinium (Gd3+), but was significantly larger when examined in cells preshrunk by negative pressure applied via the recording pipette. IL-1beta alone did not cause changes in cell volume nor in the mechanosensitivity of MNCs. We conclude that IL-1beta directly excites MNCs via an IL-1R1-mediated induction of PGE2 synthesis and EP4 receptor-dependent autocrine upregulation of the nonselective cation conductance that underlies osmoreception.
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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) | 0.002 | 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".