Generation, Characterization, and Multilineage Potency of Mesenchymal-Like Progenitors Derived from Equine Induced Pluripotent Stem Cells
Bibliographic record
Abstract
Multipotent mesenchymal stromal cells (MSCs) are more and more frequently used to treat orthopedic injuries in horses. However, these cells are limited in their expandability and differentiation capacity. Recently, the first equine-induced pluripotent stem cell (iPSC) lines were reported by us [ 1 ]. In vitro differentiation of iPSCs into MSC-like cells is an attractive alternative to using MSCs derived from other sources, as a much larger quantity of patient-specific cells with broad differentiation potential could be generated. However, the differentiation capacity of iPSCs to MSCs and the potential for use in tissue engineering have yet to be explored. In this study, equine iPSCs were induced to differentiate into an MSC-like population. Upon induction, the iPSCs changed morphology toward spindle-shaped cells similar to MSCs. The ensuing iPSC-MSCs exhibited downregulation of pluripotency-associated genes and an upregulation of MSC-associated genes. In addition, the cells expressed the same surface markers as MSCs derived from equine umbilical cord blood. We then assessed the multilineage differentiation potential of iPSC-MSCs. Although chondrogenesis was not achieved after induction with transforming growth factor-beta 3 (TGFβ3) and/or bone morphogenic protein 4 (BMP-4) in 3D pellet culture, mineralization characteristic of osteogenesis and lipid droplet accumulation characteristic of adipogenesis were observed after chemical induction. We demonstrate a protocol for the derivation of MSC-like progenitor populations from equine iPS cells.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".