Bibliographic record
Abstract
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 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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".