Increased mast cell numbers in a calcaneal tendon overuse model
Bibliographic record
Abstract
Tendinopathy is often discovered late because the initial development of tendon pathology is asymptomatic. The aim of this study was to examine the potential role of mast cell involvement in early tendinopathy using a high-intensity uphill running (HIUR) exercise model. Twenty-four male Wistar rats were divided in two groups: running group (n = 12); sedentary control group (n = 12). The running-group was exposed to the HIUR exercise protocol for 7 weeks. The calcaneal tendons of both hind limbs were dissected. The right tendon was used for histologic analysis using Bonar score, immunohistochemistry, and second harmonic generation microscopy (SHGM). The left tendon was used for quantitative polymerase chain reaction (qPCR) analysis. An increased tendon cell density in the runners were observed compared to the controls (P = 0.05). Further, the intensity of immunostaining of protein kinase B, P = 0.03; 2.75 ± 0.54 vs 1.17 ± 0.53, was increased in the runners. The Bonar score (P = 0.05), and the number of mast cells (P = 0.02) were significantly higher in the runners compared to the controls. Furthermore, SHGM showed focal collagen disorganization in the runners, and reduced collagen density (P = 0.03). IL-3 mRNA levels were correlated with mast cell number in sedentary animals. The qPCR analysis showed no significant differences between the groups in the other analyzed targets. The current study demonstrates that 7-week HIUR causes structural changes in the calcaneal tendon, and further that these changes are associated with an increased mast cell density.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".