Mesenchymal stromal cells derived from various tissues: Biological, clinical and cryopreservation aspects
Bibliographic record
Abstract
Originally isolated from bone marrow, mesenchymal stromal cells (MSCs) have since been obtained from various fetal and post-natal tissues and are the focus of an increasing number of clinical trials. Because of their tremendous potential for cellular therapy, regenerative medicine and tissue engineering, it is desirable to cryopreserve and bank MSCs to increase their access and availability. A remarkable amount of research and resources have been expended towards optimizing the protocols, freezing media composition, cooling devices and storage containers, as well as developing good manufacturing practices in order to ensure that MSCs retain their therapeutic characteristics following cryopreservation and that they are safe for clinical use. Here, we first present an overview of the identification of MSCs, their tissue sources and the properties that render them suitable as a cellular therapeutic. Next, we discuss the responses of cells during freezing and focus on the traditional and novel approaches used to cryopreserve MSCs. We conclude that viable MSCs from diverse tissues can be recovered after cryopreservation using a variety of freezing protocols, cryoprotectants, storage periods and temperatures. However, alterations in certain functions of MSCs following cryopreservation warrant future investigations on the recovery of cells post-thaw followed by expansion of functional cells in order to achieve their full therapeutic potential.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".