Isolation, Culture, Identification and Differentiation of Canine Amniotic Mesenchymal Stem Cells in Vitro
Bibliographic record
Abstract
Recent years, people are paying more and more attention to amniotic membrane tissue which has a rich resource and no ethical restrictions. Canine amniotic mesenchymal stem cells (cAMSCs) were collected by enzyme digestion method from canine amniotic membrane tissues. The cell morphology was continuously observed at different passages and cell growth curves of passage 3 and passage 9 were drawed. Stem cell related proteins and genes were identified by immunofluorescence and RT-PCR. The multiple differentiation potential of cAMSCs was identified by osteogenesis and adipogenesis. This study showed that the cAMSCs was long fusiform and could be continuously subcultured in vitro. The immunofluorescence results showed that Vimentin and SSEA-4 were positively expressed. The RT-PCR results showed that stem cell related genes OCT4, SOX2 and NANOG were positively expressed too. The cAMSCs could be induced to osteoblasts and adipocytes in vitro. The markers associated with osteogenesis and adipogenesis, such as COL1A1 and LPL, were positively expressed after differentiation. The results showed that the cAMSCs could be successfully isolated and cultured in vitro. Stem cell related proteins and genes were positively expressed. And the cAMSCs has the multiple differentiation potential. This study showed that cAMSCs could be a rich source of stem cells in veterinary. Furthermore, cAMSCs may be useful as a cell therapy application for veterinary 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 | 0.001 |
| 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".