Mast Cell Degranulation Alters Lymphatic Contractile Activity Through Action of Histamine
Bibliographic record
Abstract
OBJECTIVE: Mast cells reside in most tissues and in close association with blood vessels and nerves, areas where lymphatic vessels are also present. Mast cells and lymphatic vessels are two important players in the development of the inflammatory process. This study was designed to examine the effects of mast cell degranulation on the contractile activity of mesenteric lymphatic vessels. METHODS: Lymphatic vessel contractile activity was assessed in vitro by video microscopy of the mesentery of cow's milk-sensitized guinea pigs upon application of beta-lactoglobulin and compared to the response measured in sham animals. RESULTS: Application of 5-10 microM beta-lactoglobulin increased lymphatic vessel constriction frequency and decreased constriction amplitude (n = 12). This effect was not seen in sham-treated animals (n = 16) and was not due to an increased number of mast cells in the mesentery of the milk-sensitized animals, as revealed by histological examination. Two known mast cell-derived mediators, histamine and thromboxane A2, via stable mimetic U46619 also altered lymphatic pumping in a similar manner, but only pretreatment with the histamine H1 receptor antagonist pyrilamine (1 microM) could reduce the beta-lactoglobulin-induced response. The thromboxane A2 receptor antagonist, SQ 29548, and the 5-lipoxygenase inhibitor, caffeic acid, were without significant effect. CONCLUSION: In the in vitro mesenteric preparation, mast cell degranulation altered lymphatic contractile activity via the release of a mediator suggested to be histamine and the subsequent activation of H1 receptors. This action could potentially interfere with the expected ability of lymphatic vessels to reduce edema during inflammation.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".