Responders vs. non-responders to mesenchymal stromal cells in knee osteoarthritis patients: mechanistic correlates of donor cell attributes and putative patient features
Bibliographic record
Abstract
SUMMARY Mesenchymal stromal cell (MSC) injection has afforded heterogenous outcomes in knee osteoarthritis (KOA). Herein, a framework that dually correlates KOA patient responsiveness to baseline autologous bone m arrow-derived MSC(M) donor batch attributes and baseline clinical and biomarker features is provided. Using clinical trial data, we demonstrated that MSC(M) with increased immunomodulatory potency are more efficacious. Multivariable MSC(M) genes correlated strongly with responder status and to 12- and 24-month improvements in Knee Injury and Osteoarthritis Outcome Scores. Responder MSC(M) donor batches had unique microRNA expression and ability to polarize CD14 + monocytes in vitro . KOA Responders had lower baseline physical activity and trended toward more severe baseline KOA. Baseline local but not systemic biomarkers showed trending correlations to patient responsiveness. 42% of KOA patients were Responders at 24 months, emphasizing durability of single MSC(M) injections. Together, our analytical methodology defines critical quality attributes of potent MSC(M) donor batches and identifies putative KOA patient theratypes to MSC treatments. Graphical Abstract
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".