Development of Reproducible and Scalable Culture Conditions for In Vitro Maintenance of Pig Embryonic Stem Cells Using the Sandoz Inbred Swiss Mouse Thioguanine-Resistant Ouabain-Resistant Cell Line as a Feeder Layer
Bibliographic record
Abstract
Feeder cells play a crucial role in maintaining the pluripotency of embryonic stem cells (ESCs) by secreting various extrinsic regulators, such as extracellular matrix (ECM) proteins and growth factors. Although primary mouse embryonic fibroblasts (MEFs) are the most widely used feeder cell type for the culture of ESCs, they have inevitable disadvantages such as batch-to-batch variation and labor-intensive isolation processes. Here, we revealed that the Sandoz inbred Swiss Mouse (SIM) thioguanine-resistant ouabain-resistant (STO) cell line, an immortalized cell line established from mouse SIM embryonic fibroblasts, can be used as a feeder layer for in vitro culture of authentic pig ESCs instead of primary MEFs. First, the expression of genes encoding ECM proteins and growth factors was analyzed to compare their secretory functions as feeder cells. Quantitative real-time polymerase chain reaction (qPCR) showed that the gene expression of these pluripotency-associated factors was downregulated in STO cells compared to primary MEFs of similar density. Therefore, subsequent optimization of the culture conditions was attempted using higher STO cell densities. Notably, pig ESCs cultured on STO cell density of 3 × (187,500 cells/cm2) exhibited the most similar pluripotent state to pig ESCs cultured on primary MEF density of 1 × (62,500 cells/cm2), as determined by alkaline phosphatase staining, qPCR, and immunocytochemistry. In addition, pig ESCs cultured on STO cell density of 3 × formed complex teratoma containing multiple types of tissues derived from all three germ layers. Our culture conditions using optimal STO cell density can be applied to fields requiring reproducible and scalable production of pig ESCs, such as preclinical research and cellular agriculture.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".