Adipocyte hyperplasia: the primary mechanism of supraspinatus intramuscular fat accumulation after a complete rotator cuff tendon tear: a study in the rabbit
Bibliographic record
Abstract
Intramuscular fat (IMF) accumulates in muscles of the rotator cuff after tendon tear. The number and cross-sectional area of fat clumps and of adipocytes were quantified on osmium tetroxide stained sections of the proximal, middle and distal quarters of SSP muscles 4, 8 and 12 weeks after SSP tendon division in a rabbit model. Linear mixed-effects models were fitted to the data and statistical significance was evaluated by ANOVA. Both the number (P<0.001) and cross-sectional area (P<0.0005) of fat clumps increased after tendon detachment while time had no significant effect (both at P>0.01). IMF accumulation was more important in the distal quarter of detached SSP muscle near tendon sectioning and characterized by increases of the number (P<0.0005) and cross-sectional area of fat clumps (P<0.0005) compared to the proximal quarter. Adipocyte number increased after tendon detachment (P<0.0005) and over time (P<0.01). The cross-sectional area of adipocytes increased in the detached group compared to controls (P<0.01) while time had no significant effect (P>0.01). Interestingly, the number of adipocytes in the distal quarter increased (P<0.0005) but the cross-sectional area was smaller (P<0.0005) compared to adipocytes in the proximal quarter. Adipocyte hyperplasia localized near tendon sectioning was the main contributor to fat accumulation in the detached SSP muscles.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".