Translating stem cell therapies: The role of companion animals in regenerative medicine
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
Veterinarians and veterinary medicine have been integral to the development of stem cell therapies. The contributions of large animal experimental models to the development and refinement of modern hematopoietic stem cell transplantation were noted nearly five decades ago. More recent advances in adult stem cell/regenerative cell therapies continue to expand knowledge of the basic biology and clinical applications of stem cells. A relatively liberal legal and ethical regulation of stem cell research in veterinary medicine has facilitated the development and in some instances clinical translation of a variety of cell-based therapies involving hematopoietic stem cells and mesenchymal stem cells, as well as other adult regenerative cells and recently embryonic stem cells and induced pluripotent stem cells. In fact, many of the pioneering developments in these fields of stem cell research have been achieved through collaborations of veterinary and human scientists. This review aims to provide an overview of the contribution of large animal veterinary models in advancing stem cell therapies for both human and clinical veterinary applications. Moreover, in the context of the "One Health Initiative," the role veterinary patients may play in the future evolution of stem cell therapies for both human and animal patients will be explored.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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