Equine Induced Pluripotent Stem Cells have a Reduced Tendon Differentiation Capacity Compared to Embryonic Stem Cells
Bibliographic record
Abstract
Tendon injuries occur commonly in horses and their repair through scar tissue formation predisposes horses to a high rate of re-injury. Pluripotent stem cells may provide a cell replacement therapy to improve tendon tissue regeneration and lower the frequency of re-injury. We have previously demonstrated that equine embryonic stem cells (ESCs) differentiate into the tendon cell lineage upon injection into the damaged horse tendon and can differentiate into functional tendon cells in vitro to generate artificial tendons. Induced pluripotent stem cells (iPSCs) have now been derived from horses but, to date, there are no reports on their ability to differentiate into tendon cells. As iPSCs can be produced from adult cell types, they provide a more accessible source of cells than ESCs, which require the use of horse embryos. The aim of this study was to compare tendon differentiation by ESCs and iPSCs produced through two independent methods. In two-dimensional differentiation assays, the iPSCs expressed tendon-associated genes and proteins, which were enhanced by the presence of transforming growth factor-β3. However, in three-dimensional (3D) differentiation assays, the iPSCs failed to differentiate into functional tendon cells and generate artificial tendons. These results demonstrate the utility of the 3D in vitro tendon assay for measuring tendon differentiation and the need for more detailed studies to be performed on equine iPSCs to identify and understand their epigenetic differences from pluripotent ESCs prior to their clinical application.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".