Insulin-Like Growth Factor I Does Not Drive New Bone Formation in Experimental Arthritis
Bibliographic record
Abstract
INTRODUCTION: Insulin like growth factor (IGF)-I can act on a variety of cells involved in cartilage and bone repair, yet IGF-I has not been studied extensively in the context of inflammatory arthritis. The objective of this study was to investigate whether IGF-I overexpression in the osteoblast lineage could lead to increased reparative or pathological bone formation in rheumatoid arthritis and/or spondyloarthritis respectively. METHODS: Mice overexpressing IGF-I in the osteoblast lineage (Ob-IGF-I+/-) line 324-7 were studied during collagen induced arthritis and in the DBA/1 aging model for ankylosing enthesitis. Mice were scored clinically and peripheral joints were analysed histologically for the presence of hypertrophic chondrocytes and osteocalcin positive osteoblasts. RESULTS: 90-100% of the mice developed CIA with no differences between the Ob-IGF-I+/- and non-transgenic littermates. Histological analysis revealed similar levels of hypertrophic chondrocytes and osteocalcin positive osteoblasts in the ankle joints. In the DBA/1 aging model for ankylosing enthesitis 60% of the mice in both groups had a clinical score 1<. Severity was similar between both groups. Histological analysis revealed the presence of hypertrophic chondrocytes and osteocalcin positive osteoblasts in the toes in equal levels. CONCLUSION: Overexpression of IGF-I in the osteoblast lineage does not contribute to an increase in repair of erosions or syndesmophyte formation in mouse models for destructive and remodeling arthritis.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".