Multistep IgE Mast Cell Desensitization Is a Dose- and Time-Dependent Process Partially Regulated by SHIP-1
Bibliographic record
Abstract
Multistep mast cell desensitization blocks the release of mediators following IgE crosslinking with increasing doses of Ag. Although its in vivo application has led to the safe reintroduction of drugs and foods in IgE-sensitized patients at risk for anaphylaxis, the mechanisms of the inhibitory process have remained elusive. We sought to investigate the kinetics, membrane, and cytoskeletal changes and to identify molecular targets. IgE-sensitized wild-type murine (WT) and FcεRIα humanized (h) bone marrow mast cells were activated and desensitized with DNP, nitrophenyl, dust mites, and peanut Ags. The movements of membrane receptors, FcεRI/IgE/Ag, actin, and tubulin and the phosphorylation of Syk, Lyn, P38-MAPK, and SHIP-1 were assessed. Silencing SHIP-1 protein was used to dissect the SHIP-1 role. Multistep IgE desensitization of WT and transgenic human bone marrow mast cells blocked the release of β-hexosaminidase in an Ag-specific fashion and prevented actin and tubulin movements. Desensitization was regulated by the initial Ag dose, number of doses, and time between doses. FcεRI, IgE, Ags, and surface receptors were not internalized during desensitization. Phosphorylation of Syk, Lyn, p38 MAPK, and SHIP-1 increased in a dose-response manner during activation; in contrast, only SHIP-1 phosphorylation increased in early desensitization. SHIP-1 phosphatase function had no impact on desensitization, but silencing SHIP-1 increased β-hexoxaminidase release, preventing desensitization. Multistep IgE mast cell desensitization is a dose- and time-regulated process that blocks β-hexosaminidase, impacting membrane and cytoskeletal movements. Signal transduction is uncoupled, favoring early phosphorylation of SHIP-1. Silencing SHIP-1 impairs desensitization without implicating its phosphatase 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 | 0.001 |
| 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) | 0.002 | 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".