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Record W2060945897 · doi:10.1007/s00005-008-0041-2

Positive and negative regulatory mechanisms in high-affinity IgE receptor-mediated mast cell activation

2008· review· en· W2060945897 on OpenAlexaff
Kristy Roth, Wei‐Min Chen, Tong‐Jun Lin

Bibliographic record

VenueArchivum Immunologiae et Therapiae Experimentalis · 2008
Typereview
Languageen
FieldImmunology and Microbiology
TopicMast cells and histamine
Canadian institutionsDalhousie University
Fundersnot available
KeywordsImmunoglobulin ECell biologyMast cellAllergic inflammationDephosphorylationSignal transductionEffectorReceptorPhosphorylationPhosphataseInflammationChemistryBiologyImmunologyAntibodyBiochemistry

Abstract

fetched live from OpenAlex

Mast cells are important effector cells in allergic inflammatory reactions. The aggregation of the high-affinity IgE receptor (FcepsilonRI) on the surface of mast cells initiates a complex cascade of signaling events that ultimately leads to the release of various mediators involved in allergic inflammation and anaphylactic reactions. The release of these mediators is tightly controlled by signaling pathways that are propagated through the cell by specific phosphorylation and dephosphorylation events. These events are controlled by protein kinases and protein phosphatases which either positively or negatively regulate the propagation of the signal through the cell. This review summarizes the role of both positive and negative regulators of FcepsilonRI-induced mast cell activation.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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.

Opus teacher head0.017
GPT teacher head0.258
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations41
Published2008
Admission routes1
Has abstractyes

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