Baboon induced pluripotent stem cell generation by<i>piggyBac</i>transposition of reprogramming factors
Bibliographic record
Abstract
Abstract. Clinical application of regenerative therapies using embryonic or induced pluripotent stem cells is within reach. Progress made during recent years has encouraged researchers to address remaining open questions in order to finally translate experimental cell replacement therapies into application in patients. To achieve this, studies in translationally relevant animal models are required to make the final step to the clinic. In this context, the baboon (Papio anubis) may represent a valuable nonhuman primate (NHP) model to test cell replacement therapies because of its close evolutionary relationship to humans and its large body size. In this study, we describe the reprogramming of adult baboon skin fibroblasts using the piggyBac transposon system. Via transposon-mediated overexpression of six reprogramming factors, we generated five baboon induced pluripotent stem cell (iPSC) lines. The iPSC lines were characterized with respect to alkaline phosphatase activity, pluripotency factor expression analysis, teratoma formation potential, and karyotype. Furthermore, after initial cocultivation with mouse embryonic fibroblasts, we were able to adapt iPSC lines to feeder-free conditions. In conclusion, we established a robust and efficient protocol for iPSC generation from adult baboon fibroblasts.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".