Umbilical cord-derived stem cells (ModulatistTM) show strong immunomodulation capacity compared to adipose tissue-derived or bone marrow-derived mesenchymal stem cells
Bibliographic record
Abstract
Mesenchymal stem cells (MSCs) show great promise in regenerative medicine. Clinical applications of MSCs have recently increased significantly, especially for immune diseases. Autologous transplantation is considered a safe therapy. However, its main disadvantages are poor stability and quality of MSCs from patient to patient, and labor-intensive and time-consuming culture procedures. Therefore, allogeneic MSC transplantation has recently emerged as a potential replacement for autologous transplantation. “Off the shelf” MSC products, or socalled “stem cell drugs”, have rapidly developed; these products have already been approved in various countries, including Canada, Korea and Japan. This study aims to evaluate a new stem cell product or “drug”, termed ModulatistTM, derived from umbilical cord mesenchymal stem cells (UCMSCs), which have strong immunomodulatory properties, compared to bone marrow-derived MSCs (BMMSCs) or adipose tissue-derived stem cells (ADSCs). ModulatistTMwas produced from MSCs derived from whole umbilical cord (UC) tissue (which includes Wharton’s jelly and UC), according to GMP compliant procedures. Bone marrow- and adipose tissue-derived MSCs were isolated and proliferated in standard conditions, according to GMP compliant procedures. Immunomodulation mediated by MSCs was assessed by allogenic T cell suppression and cytokine release; role of prostaglandin E2 in the immunomodulation was also evaluated. The results showed that ModulatistTM exhibited stronger immunomodulation than BMMSC and ADSC in vitro. ModulatistTM strongly suppressed allogeneic T cells proliferation and decreased cytokine production, compared to BMMSCs and ADSCs. ModulatistTM is a strong immunomodulator and promising MSC product. It may be useful to modulate or treat autoimmune diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".