Derivation and Characterization of Canine Embryonic Stem Cell Lines with In Vitro and In Vivo Differentiation Potential
Bibliographic record
Abstract
Embryonic stem cells (ESCs) represent permanent cell lines that can be maintained in an undifferentiated state. In an environment that induces differentiation, they form derivatives of the three embryonic germ layers: mesoderm, ectoderm, and endoderm. These characteristics give ESCs great potential for both basic research and clinical applications in the areas of regenerative medicine and tissue engineering. The establishment of ESCs from large animals that model human diseases is of significant importance. We describe the derivation of permanent canine cell lines from preimplantation-stage embryos. Similar to human ESCs, canine ESCs expressed OCT3/4, NANOG, SOX2, SSEA-3, SSEA-4, TRA-1-60, TRA-1-81, and alkaline phosphatase, whereas they expressed very low levels of SSEA-1. They maintained a normal karyotype and morphology typical of undifferentiated ESCs after multiple in vitro passages and rounds of cryopreservation. Plating cells in the absence of a feeder layer, either in attachment or suspension culture, resulted in the formation of embryoid bodies and their differentiation to multiple cell types. In vivo, canine ESCs gave rise to teratomas comprising cell types of all three embryonic germ layers. These cells represent the first pluripotent canine ESC lines with both in vitro and in vivo differentiation potential and offer the exciting possibility of testing the efficacy and safety of ESC-based therapies in large animal models of human disease.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".