Nerve-mast cell (RBL) interaction: RBL membrane ruffling occurs at the contact site with an activated neurite
Bibliographic record
Abstract
Mast cell-neurite interaction serves as a model for neuroimmune interaction. We have shown that neurite-mast cell communication can occur via substance P interacting with neurokinin (NK)-1 receptors on the mucosal mast cell-like cell, the rat basophilic leukemia (RBL) cell. Neurite (murine superior cervical ganglia) and RBL cell [expressing the granule-associated antigen CD63-green fluorescent protein (GFP) conjugate] cocultures were established and stimulated with bradykinin (BK; 10 nM) or scorpion venom (SV; 10 pg/ml), both of which activate only neurites. Cell activation was assessed by confocal imaging of Ca2+ (cells preloaded with fluo 3), and analyses of RBL CD63-GFP+ granule movement were conducted. Neurite activation by BK or SV was followed by RBL Ca2+ mobilization, which was inhibited by an NK-1 receptor antagonist (NK-1 RA). Moreover, membrane ruffling was observed on RBL pseudopodial extensions in contact with the activated neurite, but not on noncontacting pseudopodia. RBL membrane ruffling was inhibited by NK-1 RA, but not NK-2 RA, and was accompanied by a significant increase in granule movement (0.13 +/- 0.04 vs. 0.05 +/- 0.01 microm/s) that was most evident at the point of neurite contact: many of the granules moved toward the plasmalemma. This is the first documentation of such precise (restricted to the membrane's contact site) transfer of information between nerves and mast cells that could allow for very subtle in vivo communication between these two cell types.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".