P2Y<sub>13</sub> and P2X<sub>7</sub> receptors modulate mechanically induced adenosine triphosphate release from mast cells
Bibliographic record
Abstract
Abstract Subcutaneous mast cells (MCs) are vulnerable to mechanical stimulation from external environment. Thus, MCs immune function could be modulated by their mechanosensitivity. This property has been identified as the trigger mechanism of needling acupuncture, a traditional oriental therapy. Previously we have demonstrated the release of adenosine triphosphate (ATP), a stress‐responsive signalling molecule, from mechanical‐perturbed MCs. The current work explores its underlying mechanisms. We noticed that propagation of intracellular free Ca 2+ occurred among HMC‐1 cells in response to 50% hypotonic shock. Additionally, amplifying cascade of ATP‐induced ATP release was observed in RBL‐2H3 cells stimulated by medium displacement, which could be mimicked by exogenous ATP (exoATP). Secondary ATP liberation induced by low level (50 nmol/L) of exoATP was reduced by inhibiting ecto‐ATPase‐dependent ADP production with ARL67156, or blocking P2 receptors with suramin or PPADS, or with specific P2Y 13 receptor antagonist MRS2211, or siRNA. Secondary ATP release induced by higher dose (200 μmol/L) of exoATP, sufficient to stimulate P2X 7 receptor, was attenuated by suramin, PPADS or specific P2X 7 receptor antagonist BBG, or siRNA. Finally, RT‐PCR confirmed mRNA expression of P2Y 13 and P2X 7 in RBL‐2H3 cells. Additionally, such secondary ATP release was attenuated by DPCPX, specific antagonist of adenosine A1 receptor, but not by MRS2179, specific inhibitor of P2Y 1 receptor. In summary, mechanosensitive ATP release from MCs is facilitated by paracrine/autocrine stimulation of P2Y 13 and P2X 7 receptors. This multi‐receptor combination could mediate transmission of information from a local site to distal areas, enabling communication with multiple surrounding cells to coordinate and synchronize their function.
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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) | 0.003 | 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".