Nuclear transfer reprogramming does not improve the low developmental potency of embryonic stem cells induced by long-term culture
Bibliographic record
Abstract
Epigenetic states of embryonic stem (ES) cells are easily altered by long-term cultivation and lose their developmental potential. To rescue this reduced developmental capacity, nuclear transfer (NT) of ES cells was carried out, and original ES and ES cells from cloned blastocysts (ntES) cells established after NT were compared with in vitro differentiation ability and developmental potential by embryoid body formation and tetraploid aggregation respectively. In the establishment of ntES cell lines, the oocytes fused with the ES cell were activated, and further cultured to cloned blastocysts. When in vitro differentiation ability was examined between original and ntES cell lines derived from ES cells with extensive passages (ES-ep), the day of appearance of simple embryoid body, cystic embryoid body, and spontaneous beating was almost similar. The developmental rates of ES-ep cells, that aggregated with tetraploid embryos to term, ranged from 3 to 6%. Moreover, the majority of live pups died soon after birth. In the ntES cell lines derived from ES-ep cells, developmental rates ranged from 0 to 5%. Those pups also died soon after birth, similar to the ES-ep-derived pups. These results suggest that profound epigenetic modifications of ES cells were retained in the re-established cell lines by NT.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".