Expectations and limitations of ovarian tissue transplantation
Bibliographic record
Abstract
Constant progress in the diagnosis and treatment of cancer disease has increased the number and prognosis of cancer survivors. However, the toxic effects of chemotherapy and radiotherapy on ovarian function have resulted in premature ovarian failure. Patients are, therefore, still expecting methods to be developed to preserve their fertility successfully. Several potential options are available to preserve fertility in patients who face premature ovarian failure, including immature or mature oocyte and embryo cryopreservation. However, for children or prepubertal women needing immediate chemotherapy, cryopreservation of ovarian tissue is the only alternative. The ultimate aim of this strategy is to implant ovarian tissue into the pelvic cavity (orthotopic site) or in a heterotopic site once oncological treatment is completed and the patient is disease free. Transplantation of ovarian tissue with sufficiently large numbers of follicles could potentially restore endocrine function and allow multiple cycles for conception. However, the success of ovarian tissue transplantation still has multiple challenges, such as the low number of follicles in the graft that may affect their longevity as well as the survival of the tissue during ex vivo processing and subsequent transplantation. Therefore, this review aims to summarize the achievements of ovary grafting and the potential techniques that have been developed to improve ovarian graft survival.
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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) | 0.001 | 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".