Induced Pluripotent Stem Cell Lines Derived from Equine Fibroblasts
Bibliographic record
Abstract
The domesticated horse represents substantial value for the related sports and recreational fields, and holds enormous potential as a model for a range of medical conditions commonly found in humans. Most notable of these are injuries to muscles, tendons, ligaments and joints. Induced pluripotent stem (iPS) cells have sparked tremendous hopes for future regenerative therapies of conditions that today are not possible to cure. Equine iPS (EiPS) cells, in addition to bringing promises to the veterinary field, open up the opportunity to utilize horses for the validation of stem cell based therapies before moving into the human clinical setting. In this study, we report the generation of iPS cells from equine fibroblasts using a piggyBac (PB) transposon-based method to deliver transgenes containing the reprogramming factors Oct4, Sox2, Klf4 and c-Myc, expressed in a temporally regulated fashion. The established iPS cell lines express hallmark pluripotency markers, display a stable karyotype even during long-term culture, and readily form complex teratomas containing all three embryonic germ layer derived tissues upon in vivo grafting into immunocompromised mice. Our EiPS cell lines hold the promise to enable the development of a whole new range of stem cell-based regenerative therapies in veterinary medicine, as well as aid the development of preclinical models for human applications. EiPS cell could also potentially be used to revive recently extinct or currently threatened equine species.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".