Specific macrophage RhoA targeting CRISPR-Cas9 for mitigating osteoclastogenesis-induced joint damage in inflammatory arthritis
Bibliographic record
Abstract
Rheumatoid arthritis (RA) is the most prevalent inflammatory arthritis with unknown etiology, characterized by synovial inflammation and articular bone erosion. Studies have highlighted that inhibiting macrophage-induced osteoclastogenesis holds promise in mitigating bone destruction. However, specifically halting this pathological cascade remains a challenge for the management of RA. Here, initially, we identify that Ras homolog gene family member A (RhoA) is a pivotal target in inducing osteoclastogenesis of macrophages. Subsequently, we develop a strategy termed specific macrophages RhoA targeting (SMART), in which phosphatidylserine (PS)-enriched macrophage membranes are engineered to deliver macrophage-specific promoter-containing CRISPR-Cas9 plasmids (SMART-Cas9), enabling targeted editing of RhoA in RA joint macrophages. Multiscale imaging techniques confirm the highly specific targeted effect of SMART-Cas9 on the macrophages of inflamed joints. SMART-Cas9 successfully reduces osteoclastogenesis by macrophages, thus mitigating bone erosion by modulating cytoskeletal dynamics and immune balance in inflammatory arthritis, representing a therapeutic avenue for RA and other inflammatory bone diseases.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".