Restoration of fertility by orthotopic transplantation of frozen adult mouse ovaries
Bibliographic record
Abstract
BACKGROUND: Successful thawing and orthotopic transplantation of ovarian tissue has produced live offspring in mice, but until now has only been successful for very young ovary donors. METHODS: Whole and half ovaries from adult C3H/HeNCrlBR (C3H) and whole ovaries from B6129SF1/J were frozen-thawed and then grafted orthotopically into B6C3F1/CrlBR (B6C3F1) and B6129SF1/J recipients, respectively. In bilateral transplant groups (bilateral), recipients underwent a bilateral ovariectomy, followed by orthotopic grafting. In unilateral groups recipients either underwent bilateral ovariectomy followed by unilateral grafting (unilateral(ovx)) or had only one ovary removed and replaced with a graft (unilateral) along with complete transection of the remaining oviduct. RESULTS: Ovary size and number of follicles decreased dramatically in grafted compared with control groups, but the loss in the unilateral(ovx) group was significantly less than in the unilateral group. Similar numbers of litters and litter size were obtained in bilateral and unilateral grafts of fresh ovary. However, a much lower number of litters and litter size were derived from unilateral grafts than from unilateral(ovx) grafts of frozen ovary. CONCLUSIONS: Normal fertility can be restored by orthotopic grafting of fresh or frozen adult mouse ovaries and no significant difference between fresh and frozen ovaries was found. Grafting of half ovaries does not alter the overall fertility rate. Unilateral(ovx) grafting is an efficient procedure to produce live pups and removes the negative effect of recipient native ovaries on post-grafting fertility.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".