Insulin-dependent diabetes impairs the inflammatory response and delays angiogenesis following Achilles tendon injury
Bibliographic record
Abstract
Although impaired wound healing associated with type 1 diabetes mellitus has been well studied in skin tissue, the influence of this metabolic disorder on tendon healing and recovery has not been extensively investigated. Because tendons are known to have limited repair potential, we studied the tendon-healing process by using a diabetic rat tendonitis model. We tested the hypothesis that diabetes influences the inflammatory response, cell proliferation, and angiogenesis in injured Achilles tendons. Diabetes was induced by injecting streptozotocin at 45 mg/kg body wt. Non-diabetic rats as well as diabetic and insulin-treated diabetic animals were then injected with collagenase. The accumulation of inflammatory cells was quantified in transversal sections of Achilles tendon by using immunohistochemical staining at days 0, 1, 3, 7, 14, and 28 posttrauma. The number of proliferative cells and the extent of neovascularization was also quantified in the paratenon and the core of the tendon at days 0, 3, 7, 14, and 28 posttrauma. Relative to nondiabetic and insulin-treated diabetic animals, the numbers of accumulated neutrophils and ED1(+) and ED2(+) macrophages in diabetic rats decreased by 46, 43, and 52%, respectively, in the first 3 days after injury compared with levels in nondiabetic and insulin-treated diabetic animals. The density of newly formed blood vessels decreased by 35 and 29% in the paratenon and the core of tendon, respectively, at days 3 and 7 after injury. Lastly, the concentration of proliferative cells decreased by 34% in the paratenon at day 7 posttrauma in injured tendons from diabetic rats relative to nondiabetic rats. These results indicate that alterations in inflammatory, angiogenic, and proliferative processes occurred in the diabetic state that might eventually perturb tendon healing and remodeling.
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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 | 0.001 |
| 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".