Prodrug Nanomedicine for Synovium Targeted Therapy of Inflammatory Arthritis: Insights from Animal Model and Human Synovial Joint Fluid
Bibliographic record
Abstract
Abstract Many patients cannot tolerate low‐dose weekly methotrexate (MTX) therapy for inflammatory arthritis treatment due to life‐threatening toxicity. Although biologics offer a target‐specific therapy, it raises the risk of serious infections and even cancer due to immune system suppression. We introduce an anti‐inflammatory arthritis MTX ester prodrug using a long‐circulating biocompatible polymeric macromolecule: folic acid (FA) functionalized hyperbranched polyglycerol (HPG). In vitro the drug MTX is incrementally released through pH and enzymatic degradation over 2 weeks. The role of matrix metalloproteinases (MMPs) in site‐specific prodrug activation was verified using synovial fluid (SF) of 26 rheumatology patients and 4 healthy controls. Elevated levels of specific MMPs‐markers of joint inflammation‐positively correlated with enhanced prodrug release explained by acid‐catalyzed hydrolysis of esters by proteases. Intravenously administered 111In‐radiolabeled prodrug confirmed by SPECT/CT imaging that it accumulated preferentially in inflamed joints while reducing off‐target side‐effects in a mouse model of rheumatoid arthritis (RA). Added FA as a targeting vector prolonged prodrug action; prodrug with 4x less MTX applied every 2 weeks was as effective as weekly MTX therapy. The preclinical results suggest a prodrug‐based strategy for the treatment of inflammatory joint diseases, with potential for other chronic inflammatory diseases and cancer.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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".