Bioengineering the ovary to preserve and reestablish female fertility
Bibliographic record
Abstract
Different bioengineering strategies can be presently adopted and have been shown to have great potential in the treatment of female infertility and ovarian dysfunction deriving from chemotherapy, congenital malformations, massive adhesions as well as aging and lifestyle. One option is transplantation of fresh or cryopreserved organs/fragments into the patient. A further possibility uses tissue engineering approaches that involve a combination of cells, biomaterials and factors that stimulate local ability to regenerate/ repair the reproductive organ. Organ transplant has shown promising results in large animal models. However, the source of the organ needs to be identified and the immunogenic effects of allografts remain still to be solved before the technology may enter the clinical practice. Decellularization/ repopulation of ovary with autologous cells or follicles could represent an interesting, still very experimental alternative. Here we summarize the recent advancements in the bioengineering strategies applied to the ovary, we present the principles for these systems and discuss the advantages of these emerging opportunities to preserve or improve female fertility.
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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".