Establishment and Chimera Analysis of 129/SvEv- and C57BL/6-Derived Mouse Embryonic Stem Cell Lines
Bibliographic record
Abstract
Hundreds of new mutant mouse lines are being produced annually using gene targeting and gene trap approaches in embryonic stem (ES) cells, and the number is expected to continue to grow as the human and mouse genome projects progress. The availability of robust ES cell lines and a simple technology for making chimeras is more attractive now than ever before. We established several new ES cell lines from 129/SvEv and C57BL/6 mice and tested their ability to contribute to the germline following blastocyst injections and/or the less expensive and easier method of morula-ES cell aggregation. Using morula aggregation to produce chimeras, five newly derived 129/SvEv and two C57BL/6 ES cell lines tested at early passages were found to contribute extensively to chimeras and produce germline-transmitting male chimeras. Furthermore, the two 129S/vEv ES cell lines that were tested and one of the C57BL/6 ES cell lines were able to maintain these characteristics after many passages in vitro. Our results indicate that the ability of ES cells to contribute strongly to chimeras following aggregation with outbred embryos is a general property of early passage ES cells and can be maintained for many passages. C56BL/6-derived ES cell lines, however, have a greater tendency than 129-derived ES cell lines to lose their ability to colonize the germline.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.002 |
| 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".