Inflammation‐induced leukocyte accumulation in injured skeletal muscle: Role of mast cells
Bibliographic record
Abstract
Inflammation consequent to muscle damage is characterized by an accumulation of leukocytes. Our aim in this study was to determine whether mast cells can modulate inflammation-induced leukocyte trafficking. One approach consisted of giving rats a mast cell-degranulating agent, CMP 48/80, prior to a protocol of lengthening contractions inducing inflammation without neutrophil accumulation; in parallel, other rats were given the mast cell-stabilizing agent, cromolyn, prior to injecting muscle with bupivacaine, which induces neutrophil accumulation. Damage was evaluated through measurement of contractile force and inflammation using histochemical and immunohistochemical methods. Stimulation with CMP 48/80 increased the proportion of degranulated mast cells significantly and neutrophil accumulation occurred with lengthening contractions. With bupivacaine, accumulation of neutrophils decreased by 70% when degranulation was inhibited. These results indicate that mast cells are important in the process governing leukocyte trafficking in skeletal muscle trauma and that targeting their inhibition could be an attractive alternative for control of inflammation.
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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".