Update on the Use of Mesenchymal Stem Cells and their Products in Hematopoietic Stem Cell Transplantation
Bibliographic record
Abstract
Graft Versus Host Disease (GVHD) is a major limitation to the success of allogeneic Hematopoietic Stem Cell Transplantation (HSCT) as Steroid-Refractory (SR) acute GVHD carries poor prognosis due to the absence of an efficacious second-line therapy. Mesenchymal Stem Cells (MSCs) which have immunosuppressive, immunomodulatory, and regenerative properties may become a highly effective therapeutic modality for SR-GVHD in the near future. MSCs have already been approved to treat childhood SR-GVHD in Japan, and they have been conditionally licensed in New Zealand and Canada. It is expected that MSCs will be approved for the treatment of SR-GVHD in adults in Europe, North America, and other parts of the world within a few years. Utilization of the recently introduced techniques including the use of MSC products such as exosomes and Extracellular Vesicles (ECVs) instead of the parent MSCs, robotic manufacturing technology, and genetic engineering of MSCs will ultimately overcome the remaining obstacles facing the widespread utilization of MSCs and their products as therapeutics not only in HSCT but also in other medical fields. The aim of this review is to provide an update on the remarkable progress achieved in the use of MSCs and their products in the field of HSCT.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 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".