Normal sheep synovium has similar appearances and constitutive expression of inflammatory cytokines within and between knee joints: a baseline histological and molecular analysis
Bibliographic record
Abstract
Abstract Clinical evidence suggests that synovium can add to adjacent articular cartilage damage, potentially contributing to the development of osteoarthritis (OA). Inflammation of the synovium (synovitis) is dependent on the type of injury sustained, the time after injury and concomitant changes in other joint tissues. To define the role of synovitis in OA development, there is a need for baseline measures that can reliably distinguish synovial inflammation from normal synovium both within and between joints. This study tested the hypothesis that normal synovium from distinct anatomical locations in young and adult sheep is homogeneous with respect to consistently low molecular expression of the inflammatory mediators - tumour necrosis factor alpha (TNF-α) and interleukins (IL) such as IL-1β, IL-1Ra, IL-6 and IL-8. Additionally, maturation will not influence the expression of these select inflammatory biomarkers. Samples of synovium from four anatomic locations (medial and lateral margins, suprapatellar pouch (patella region), posterior to the posterior cruciate ligament, from each joint of 5 adult and 4 immature animals were graded histologically or analyzed for mRNA expression of inflammatory cytokines. Histologically, no evidence of synovitis was noted although some variance in sub-intimal fibrosis was observed between sample locations in mature sheep. Molecular expression of all inflammatory mediators was low and homogeneously expressed at constitutive levels in all sample locations. These findings confirm the hypothesis that the normal sheep synovium is a homogeneous tissue throughout the joint and establishes the baseline expression levels for several pro-inflammatory mediators in both immature and mature sheep.
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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 | 0.001 |
| 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".