Derivation and Characterization of Canine Embryonic Stem Cell Lines with In Vitro and In Vivo Differentiation Potential.
Bibliographic record
Abstract
Embryonic stem (ES) cells represent permanent cell lines that can be maintained in an undifferentiated state and induced to form derivatives of the three embryonic germ layers. These characteristics give ES cells great potential for both basic research and clinical applications in regenerative medicine. The establishment of ES cells from large animals that model human diseases is of significant importance. We derived permanent canine cell lines from preimplantation stage embryos. These cells expressed the core pluripotency transcription factors OCT3/4, NANOG, SOX2 and, similar to human ES cells, they expressed SSEA-3, SSEA-4, TRA-1-60, TRA-1-81. Canine ES cells maintained a normal karyotype and morphology after multiple in vitro passages and rounds of cryopreservation. Plating cells in the absence of a feeder layer resulted in their in vitro differentiation to multiple cell types. In vivo, canine ES cells gave rise to teratomas comprising cell types of the three embryonic germ layers. In an attempt to define the signaling cascades regulating cES cell self-renewal and pluripotency, we assessed the utility of the small molecule inhibitors of Mek/Erk and Gsk3 in combinations with LIF, BMP4 and bFGF for the derivation and maintenance of canine ES cells. Preliminary results suggested that although morula-stage embryos initially underwent ex vivo maturation with expansion of the inner cell mass, embryos arrested at the expanded blastocyst stage regardless of the combination of small molecules and growth factors used. Moreover, supplementation of early passage cultures with inhibitors induced proliferative arrest and cell death. Thus, the signaling pathways regulating the self-renewal of canine ES cells remain unclear. (platform)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".