Adenosine receptor A2a inhibits complement-mediated activation of human mast cells by activating G{alpha}s-proteins
Bibliographic record
Abstract
The complement anaphylatoxin 3a (C3a) and adenosine receptors (AR) are implicated in the inflammatory process in allergic rhinitis although a direct interaction between these pathways has not been demonstrated. To investigate the interaction between these pathways, primary human cultured mast cells (HuMC) and human mast cell line (LAD2) were stimulated with C3a with or without AR agonists and antagonists. The non-selective AR agonist, 5'-N-ethylcarboxamidoadenosine (NECA; 30 uM), inhibited C3a-mediated HuMC and LAD cell degranulation (43 + 4 and 40 + 5 % inhibition respectively compared to control). NECA also blocked C3a-activated production of MCP-1 (57 + 6 %) and C3a-activated chemotaxis (46.7 + 10 %). A selective A2aR agonist, CGS 21680, inhibited C3a-mediated degranulation but the A3R agonist, IB-MECA, had no effect suggesting that inhibition of degranulation was mediated by A2aR. An A2aR antagonist, SCH 58261, blocked the inhibitory effect of NECA but an A2bR and A3R antagonist had no effect. Real-time PCR analysis showed that LAD2 and HuMC expressed mRNA for A2aR, A2bR and A3R but not A1R. Measurements of intracellular cAMP showed that NECA elevated [cAMP]i levels by at least 30% even in C3a-activated cells. Pertussis toxin blocked C3a-activated degranulation. The adenylyl cyclase inhibitor, SQ 22536, had no effect on C3a-activated degranulation but blocked the effect of NECA demonstrating that C3a and NECA mediate their effects through Gi and Gs proteins respectively. These results show that adenosine inhibits complement activation of human mast cells through a Gs-protein pathway.
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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) | 0.002 | 0.001 |
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".