Regional quantification of cartilage type II collagen and aggrecan messenger RNA in joints with early experimental osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: Accurate assessment of chondrocyte metabolism is a potentially valuable indicator of cartilage health in osteoarthritis (OA). This study was conducted to explore the anabolic metabolism of chondrocytes early in the natural history of an experimental canine model of OA. METHODS: Competitive reverse transcription-polymerase chain reaction was used to calculate the copy number of type II collagen and the messenger RNA (mRNA) levels of aggrecan core protein in articular cartilage samples obtained from different regions of the femorotibial joint 12 and 39 weeks after cruciate transection. RESULTS: Gene expression of both type II collagen and aggrecan in cartilage samples obtained from experimental joints at both intervals after surgery was elevated significantly compared with that in samples from contralateral control joints. The number of mRNA copies per microgram of DNA of aggrecan exceeded that of type II collagen in control cartilage, but the copy number of type II collagen mRNA exceeded that of aggrecan in OA cartilage. Thus, the ratio of type II collagen-to-aggrecan mRNA copy number (normalized to DNA) was shown to be characteristically altered in cartilage with experimental OA. CONCLUSION: Accurate assessment of multiple gene products in small samples of cartilage taken from focal areas of a joint can be used diagnostically for monitoring chondrocyte metabolism and possibly for staging at least the early phases of this joint disease.
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 | 0.000 | 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 | 0.001 |
| 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".