Peptide-mediated mast cell activation: ligand similarities for receptor recognition and protease-induced regulation
Bibliographic record
Abstract
Abstract MCs are crucial regulators of the innate immune response. MC degranulation is a rapid response mechanism that allows for the release of a stored plethora of inflammatory mediators, including histamine, heparin, various serine proteases, chemokines, and cytokines. The activation of MCs can lead to the de novo expression of a variety of chemokines and cytokines that can influence a variety of outcomes: inflammation, angiogenesis, and others. A variety of IgE-independent mediators, including IgG, cytokines, chemokines, exogenous molecules, drugs, and cationic peptides, and others, can directly trigger MC activation. For decades, various peptide stimuli, including peptide toxins, neuropeptides, antimicrobial peptides, and endogenous bioactive peptides, have been associated with MC allergic reactions in various physiologic and pathologic conditions. Recently, an activation mechanism has been established, whereby the MRGPRX2 receptor is involved in most of the peptide stimuli-related activation of human MCs. Interestingly, most of these peptide sequences seem to have a strong structural similarity that includes abundant positive charges and aromatic/aliphatic amino acids. In this review, we discuss the structures of known peptide stimuli and the receptors with which they interact for the express purpose of highlighting peptide elements as building blocks for tissue engineering applications.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".