Apolipoprotein A1 distribution pattern in the human Achilles tendon
Bibliographic record
Abstract
Metabolic factors such as cholesterol appear to play an important role in the development of Achilles tendinopathy. There is, however, no morphologic proof explaining the link between high cholesterol and tendinopathy. As apolipoprotein A1 (Apo-A1) is essential for reverse cholesterol transport, it may be related to cholesterol overload in tendon. Nothing is known about Apo-A1 expression in tendon tissue. We examined the distribution of Apo-A1 protein in biopsies from normal and tendinopathy-affected human Achilles tendons, and APOA1 mRNA production from cultured human hamstring tenocytes. Specific immunoreactions for Apo-A1 were detected. The tenocytes showed specific Apo-A1 immunoreactions. These reactions were usually distinct in the tendinopathy specimens. While the tendinopathy specimens often showed granular/small deposit reactions, the slender tenocytes of control specimens did not show this pattern. The magnitude of Apo-A1 immunoreactivity was especially marked in the tendinopathy specimens, as there is a high number of tenocytes. Reactions were also seen in the walls of blood vessels located within the tendon tissue proper of both the normal and tendinopathy tendons and within the peritendinous/fatty tissue of the tendinopathy tendons. The reactions were predominantly in the form of deposit reactions within the smooth muscle layer of the vessel walls. Cultured hamstring tenocytes produced APOA1 mRNA. We demonstrated the presence of Apo-A1 in human tendon tissue. This suggests there may be a link between Achilles tendinopathy and cholesterol metabolism. We hypothesize that Apo-A1 may be important for tenocyte and blood vessel function within tendons.
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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 | 0.001 | 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 | 0.000 |
| 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".