Time-Dependent Recovery of Human Synovial Membrane Mesenchymal Stem Cell Function After High-Dose Steroid Therapy: Case Report and Laboratory Study
Bibliographic record
Abstract
BACKGROUND: The use of mesenchymal stem cells from various tissue sources to repair injured tissues has been explored over the past decade in large preclinical models and is now moving into the clinic. PURPOSE: To report the case of a patient who exhibited compromised mesenchymal stem cell (MSC) function shortly after use of high-dose steroid to treat Bell's palsy, who recovered 7 weeks after therapy. STUDY DESIGN: Case report and controlled laboratory study. METHODS: A patient enrolled in a first-in-human clinical trial for autologous implantation of a scaffold-free tissue engineered construct (TEC) derived from synovial MSCs for chondral lesion repair had a week of high-dose steroid therapy for Bell's palsy. Synovial tissue was harvested for MSC preparation after a 3-week recovery period and again at 7 weeks after therapy. RESULTS: The MSC proliferation rates and cell surface marker expression profiles from the 3-week sample met conditions for further processing. However, the cells failed to generate a functional TEC. In contrast, MSCs harvested at 7 weeks after steroid therapy were functional in this regard. Further in vitro studies with MSCs and steroids indicated that the effect of in vivo steroids was likely a direct effect of the drug on the MSCs. CONCLUSION: This case suggests that MSCs are transiently compromised after high-dose steroid therapy and that careful consideration regarding timing of MSC harvest is critical. CLINICAL RELEVANCE: The drug profiles of MSC donors and recipients must be carefully monitored to optimize opportunities to successfully repair damaged tissues.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".