Context-specific protection of TGFα null mice from osteoarthritis
Bibliographic record
Abstract
Transforming growth factor alpha (TGFα) is a growth factor involved in osteoarthritis (OA). TGFα induces an OA-like phenotype in articular chondrocytes, by inhibiting matrix synthesis and promoting catabolic factor expression. To better understand TGFα's potential as a therapeutic target, we employed two in vivo OA models: (1) post-traumatic and (2) aging related OA. Ten-week old and six-month old male Tgfa null mice and their heterozygous (control) littermates underwent destabilization of the medial meniscus (DMM) surgery. Disease progression was assessed histologically using the Osteoarthritis Research Society International (OARSI) scoring system. As well, spontaneous disease progression was analyzed in eighteen-month-old Tgfa null and heterozygous mice. Ten-week old Tgfa null mice were protected from OA progression at both seven and fourteen weeks post-surgery. No protection was seen however in six-month old null mice after DMM surgery, and no differences were observed between genotypes in the aging model. Thus, young Tgfa null mice are protected from OA progression in the DMM model, while older mice are not. In addition, Tgfa null mice are equally susceptible to spontaneous OA development during aging. Thus, TGFα might be a valuable therapeutic target in some post-traumatic forms of OA, however its role in idiopathic disease is less clear.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".