Changing the threshold—Signals and mechanisms of mast cell priming
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Summary Mast cells play a key role in allergy and other inflammatory diseases involving engagement of multivalent antigen with IgE bound to high‐affinity IgE receptors (FcεRIs). Aggregation of FcεRIs on mast cells initiates a cascade of signaling events that eventually lead to degranulation, secretion of leukotrienes and prostaglandins, and cytokine and chemokine production contributing to the inflammatory response. Exposure to pro‐inflammatory cytokines, chemokines, bacterial and viral products, as well as some other biological products and drugs, induces mast cell transition from the basal state into a primed one, which leads to enhanced response to IgE‐antigen complexes. Mast cell priming changes the threshold for antigen‐mediated activation by various mechanisms, depending on the priming agent used, which alone usually do not induce mast cell degranulation. In this review, we describe the priming processes induced in mast cells by various cytokines (stem cell factor, interleukins‐4, ‐6 and ‐33), chemokines, other agents acting through G protein‐coupled receptors (adenosine, prostaglandin E 2 , sphingosine‐1‐phosphate, and β‐2‐adrenergic receptor agonists), toll‐like receptors, and various drugs affecting the cytoskeleton. We will review the current knowledge about the molecular mechanisms behind priming of mast cells leading to degranulation and cytokine production and discuss the biological effects of mast cell priming induced by several cytokines.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 it