IGF‐I activates PKB and prevents anoxic apoptosis in Achilles tendon cells
Bibliographic record
Abstract
Anoxia and apoptosis are both implicated in chronic tendon pathology, however the influence of anoxia on the viability of tendon cells is not known. The objectives of the current study were to (i) investigate the effect of oxygen withdrawal on the viability of porcine Achilles tendon cells (ATCs), and (ii) examine the ability of IGF-I, a factor with known regenerative properties in tendon, to prevent ATC death. Cultured ATCs were enclosed in an anaerobic chamber. The mechanism of cell death was examined by flow cytometry of ATCs double labeled with Annexin-V and propidium iodide (PI). Caspase activity was determined by a fluorometric assay, and nuclear morphology was examined by Hoechst staining. The cell death induced by anoxia was time-dependent, and was characterized by phosphatidylserine exposure on the outer membrane, caspase activation and DNA fragmentation. Death was inhibited by the addition of IGF-I in a dose-dependent manner. The ability of IGF-I to activate the pro-survival PKB pathway in ATCs was inhibited by LY294002, indicating the importance of PI3K in the response of ATCs to IGF-I. These data suggest that cell death induced by lack of oxygen is predominantly apoptotic and can be prevented by pro-survival IGF-I signaling. This mechanism may contribute to the beneficial effect of IGF-I on tendon.
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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".