Cross talk between P2 purinergic receptors modulates extracellular ATP-mediated interleukin-10 production in rat microglial cells
Bibliographic record
Abstract
Previously we demonstrated that ATP released from LPS-activated microglia induced IL-10 expression in a process involving P2 receptors, in an autocrine fashion. Therefore, in the present study we sought to determine which subtype of P2 receptor was responsible for the modulation of IL-10 expression in ATP-stimulated microglia. We found that the patterns of IL-10 production were dose-dependent (1, 10, 100, 1,000 microM) and bell-shaped. The concentrations of ATP, ATP-gammaS, ADP, and ADP-betaS that showed maximal IL-10 release were 100, 10, 100, and 100 microM respectively. The rank order of agonist potency for IL-10 production was 2'-3'-O-(4-benzoyl)-benzoyl ATP (BzATP)=dATP>2-methylthio-ADP (2-meSADP). On the other hand, 2-methylthio-ATP (2-meSATP), alpha,beta-methylene ATP (alpha,beta-meATP), UTP, and UDP did not induce the release of IL-10 from microglia. Further, we obtained evidence of crosstalk between P2 receptors, in a situation where intracellular Ca(2+) release and/or cAMP-activated PKA were the main contributors to extracellular ATP-(or ADP)-mediated IL-10 expression, and IL-10 production was down-regulated by either MRS2179 (a P2Y(1) antagonist) or 5'-AMPS (a P2Y(11) antagonist), indicating that both the P2Y(1) and P2Y(11) receptors are major receptors involved in IL-10 expression. In addition, we found that inhibition of IL-10 production by high concentrations of ATP-gammaS (100 microM) was restored by TNP-ATP (an antagonist of the P2X(1), P2X(3), and P2X(4) receptors), and that IL-10 production by 2-meSADP was restored by 2meSAMP (a P2Y(12) receptor antagonist) or pertussis toxin (PTX; a Gi protein inhibitor), indicating that the P2X(1), P2X(3), P2X(4)receptor group, or the P2Y(12) receptor, negatively modulate the P2Y(11) receptor or the P2Y(1) receptor, respectively.
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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 | 0.000 |
| 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".