Nerve Growth Factor Activates Mast Cells Through the Collaborative Interaction with Lysophosphatidylserine Expressed on the Membrane Surface of Activated Platelets
Bibliographic record
Abstract
Effect of nerve growth factor (NGF) on platelet-associated mast cell activation was investigated. Although neither NGF alone nor platelets alone induced significant 5-hydroxytriptamine (5-HT) release from rat peritoneal mast cells, marked 5-HT release was detected when costimulated with NGF and calcium ionophore-activated platelets. This response reached maximal levels as early as 5 min after the initiation of the coincubation and was completely blocked by anti-NGF Ab or by an inhibitor for a tyrosine kinase of the trkA NGF receptor. Paraformaldehyde-fixed platelets activated with either calcium ionophore or thrombin exhibited the collaborative ability, suggesting the possible involvement of some membrane molecules expressed on activated platelets in mast cell activation. Because activation of platelets induced expression of phosphatidylserine (PS) and/or lysoPS on membrane surface, and since lysoPS, unlike PS, initiated the NGF-induced 5-HT release, lysoPS expressed on activated platelets may be involved in the mast cell activation. Moreover, intradermal injection of NGF and activated platelets into the rat skin increased local vascular permeability. These findings suggested that NGF collaboratively worked with membrane lysoPS of activated platelets to induce mast cell activation. Thus, NGF released in response to inflammatory stimuli may contribute to mast cell activation in collaboration with locally activated platelets in the process of inflammations and tissue repair.
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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".