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Mast cells and their role in the neuro‐immune‐endocrine axis

2004· article· en· W2070161278 on OpenAlexaff
John Bienenstock

Bibliographic record

VenueExperimental Dermatology · 2004
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMast cells and histamine
Canadian institutionsMcMaster University
Fundersnot available
KeywordsImmune systemMast cellNeuroscienceBiologyOrganismHomeostasisEndocrine systemCentral nervous systemInflammationCell typeSecretionHormoneNervous systemImmunologyReceptorCell biologyCellEndocrinology

Abstract

fetched live from OpenAlex

It has become clear that the immune and nervous systems communicate constantly to maintain homeostasis and a coordinated and continuing adaptive response to an ever‐changing environment. Evidence from mast cell nerve communication, as an example of this interaction, has been obtained in a variety of tissues and circumstances, most especially in the intestine and skin. Bidirectional communication has been shown in vivo , ex vivo , in vitro and in coculture experiments involving the two cell types. Examples will be given of these various situations and involve normal physiological situations and those involved in response to infection and inflammation as well as in response to ultraviolet light. More recent examples of the importance of mast cells in the regulation of central nervous activity including the secretion of hormones by the pituitary gland, and thereby the regulation of the HPA axis as well as involvement in behavioural change will be addressed. Through its potential communication with the nervous system, the mast cell can be regarded as a sentinel cell or receptor, especially located at surfaces exposed to the environment, which specifically and non‐specifically react to molecules and substances, foreign to the organism, so as to help orchestrate the complex and integrated responses required to maintain homeostasis.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.526

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.006
GPT teacher head0.210
Teacher spread0.205 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations0
Published2004
Admission routes1
Has abstractyes

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