Mesenchymal stromal cells derived from various tissues: Biological, clinical and cryopreservation aspects
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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 it