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Record W3199520454 · doi:10.3389/fimmu.2021.718499

Mast Cell Modulation of B Cell Responses: An Under-Appreciated Partnership in Host Defence

2021· review· en· W3199520454 on OpenAlexafffund
Alejandro Palma, Mark Robert Hanes, Jean S. Marshall

Bibliographic record

VenueFrontiers in Immunology · 2021
Typereview
Languageen
FieldImmunology and Microbiology
TopicMast cells and histamine
Canadian institutionsBeatrice Hunter Cancer Research InstituteIzaak Walton Killam Health CentreDalhousie University
FundersCanadian Institutes of Health ResearchIWK Health CentreBeatrice Hunter Cancer Research InstituteCancer Research Institute
KeywordsMast cellCell biologyBiologyImmune systemImmunologyReceptorInterleukin 33Acquired immune systemAntibodyInnate immune systemCytokineInterleukinGenetics

Abstract

fetched live from OpenAlex

cross-linking of immunoglobulins bound to surface receptors. They are also recognized as key initiators and regulators of both innate and adaptive immune responses against pathogens, especially in the skin and mucosal surfaces. Substantial attention has been given to the role of mast cells in regulating T cell function either directly or indirectly through actions on dendritic cells. In contrast, the ability of mast cells to modify B cell responses has been less explored. Several lines of evidence suggest that mast cells can greatly modify B cell generation and activities. Mast cells co-localise with B cells in many tissue settings and produce substantial amounts of cytokines, such as IL-6, with profound impacts on B cell development, class-switch recombination events, and subsequent antibody production. Mast cells have also been suggested to modulate the development and functions of regulatory B cells. In this review, we discuss the critical impacts of mast cells on B cells using information from both clinical and laboratory studies and consider the implications of these findings on the host response to infections.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.978
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.276
Teacher spread0.243 · 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 teacher head, not a consensus.

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

Citations35
Published2021
Admission routes2
Has abstractyes

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