An Angiogenesis Inhibitor, 2-Methoxyestradiol, Involutes Rat Collagen-Induced Arthritis and Suppresses Gene Expression of Synovial Vascular Endothelial Growth Factor and Basic Fibroblast Growth Factor
Bibliographic record
Abstract
OBJECTIVE: Rheumatoid arthritis (RA) pannus may be dependent on angiogenesis and several critical growth factors including vascular endothelial growth factor (VEGF) and basic fibroblast growth factor (bFGF). 2-Methoxyestradiol (2ME2), an endogenous metabolite with low estrogen receptor affinity, has both antiangiogenic and antiproliferative activity. 2ME2 was assessed in the rat collagen-induced arthritis (CIA) model to determine if it could prevent or involute established synovitis. METHODS: Rats were immunized on Day 0 with collagen and randomized to a vehicle control or two 2ME2 prevention arms. In additional studies, multiple parallel treatment arms were initiated at Day 10 after arthritis onset. RESULTS: 2ME2 in preventive protocols at 30 or 100 mg/kg significantly delayed the onset and reduced the severity of clinical and radiographic CIA. In established CIA, oral 2ME2 at 50 mg/kg/bid, 100 mg/kg/day, and 300 mg/kg/day reduced severity compared to vehicle controls. Efficacy of 2ME2 delivery by osmotic pumps at 60 mg/kg/day was equivalent to 300 mg/kg/day by daily gavage. The 3 oral treatment protocols all significantly reduced radiographic scores in a dose-dependent fashion, with the greatest benefit at 300 mg/kg. 2ME2 showed marked suppression of synovial gene expression of proangiogenic bFGF and VEGF, with parallel reduction of synovial blood vessels. Serum antibody levels to native type II collagen were not reduced, suggesting that 2ME2 did not influence humoral immunity. CONCLUSION: Our results indicate that 2ME2 may represent a novel agent for the treatment of inflammatory autoimmune diseases such as RA.
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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 | 0.000 | 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".