Mesenchymal‐like stem cells in canine ovary show high differentiation potential
Bibliographic record
Abstract
OBJECTIVES: Recent studies have reported the existence of stem cells in ovarian tissue that show enhanced proliferative and differentiation potential compared to other adult tissues. Based on this evidence, we hypothesized that ovarian tissue contained mesenchymal-like stem cells (MSC) that could be isolated using a novel rapid plastic adhesion technique. MATERIALS AND METHODS: We established MSC lines derived from ovarian and adipose tissue based on their ability to rapidly adhere to plastic culture dishes in the first 3 hours after plating and studied their potentiality in terms of molecular markers and differentiation capacity. RESULTS: Morphological and kinetic properties of in vitro cultured ovarian MSC were similar to adipose-derived MSC, and both reached senescence after similar passage numbers. Ovarian-derived MSC expressed mesenchymal (CD90 and CD44) but not haematopoietic markers (CD34 and CD45), indicating similarity to adipose-derived MSC. Moreover, ovarian-derived MSC expressed NANOG, TERT, SOX2, OCT4 and showed extensive capacity to differentiate not only into adipogenic, osteogenic and chondrogenic tissue but also towards neurogenic and endodermal lineages and even precursors of primordial germ cells. CONCLUSION: These results show for the first time the derivation of ovarian cells with the molecular properties of MSC as well as wide differentiation potential. Canine ovarian tissue is accessible, expandable, multipotent and has high plasticity, holding promise for applications in regenerative medicine.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".