Generation of pluripotent stem cells from eggs of aging mice
Bibliographic record
Abstract
Oocytes can reprogram genomes to form embryonic stem (ES) cells. Although ES cells largely escape senescence, oocytes themselves do senesce in the ovaries of most mammals. It remains to be determined whether ES cells can be established using eggs from old females, which exhibit reproductive senescence. We attempted to produce pluripotent stem cell lines from artificial activation of eggs (also called pES) from reproductive aged mice, to determine whether maternal aging affects pES cell production and pluripotency. We show that pES cell lines were generated with high efficiency from reproductive aged (old) mice, although parthenogenetic embryos from these mice produced fewer ES clones by initial two passages. Further, pES cell lines generated from old mice showed telomere length, expression of pluripotency molecular markers (Oct4, Nanog, SSEA1), alkaline phosphatase activity, teratoma formation and chimera production similar to young mice. Notably, DNA damage was reduced in pES cells from old mice compared to their progenitor parthenogenetic blastocysts, and did not differ from that of pES cells from young mice. Also, global gene expression differed only minimally between pES cells from young and old mice, in contrast to marked differences in gene expression in eggs from young and old mice. These data demonstrate that eggs from old mice can generate pluripotent stem cells, and suggest that the isolation and in vitro culture of ES cells must select cells with high levels of DNA and telomere integrity, and/or with capacity to repair DNA and telomeres.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".