Ovarian Decellularized Bioscaffolds Provide an Optimal Microenvironment for Cell Growth and Differentiation In Vitro
Bibliographic record
Abstract
Ovarian failure is the most common cause of infertility. Although numerous strategies have been proposed, a definitive solution for recovering ovarian functions and restoring fertility is currently unavailable. One innovative alternative may be represented by the development of an "artificial ovary" that could be transplanted in patients for re-establishing reproductive activities. Here, we describe a novel approach for successful repopulation of decellularized ovarian bioscaffolds in vitro. Porcine whole ovaries were subjected to a decellularization protocol that removed the cell compartment, while maintaining the macrostructure and microstructure of the original tissue. The obtained bioscaffolds were then repopulated with porcine ovarian cells or with epigenetically erased porcine and human dermal fibroblasts. The results obtained demonstrated that the decellularized extracellular matrix (ECM)-based scaffold may constitute a suitable niche for ex vivo culture of ovarian cells. Furthermore, it was able to properly drive epigenetically erased cell differentiation, fate, and viability. Overall, the method described represents a powerful tool for the in vitro creation of a bioengineered ovary that may constitute a promising solution for hormone and fertility restoration. In addition, it allows for the creation of a suitable 3D platform with useful applications both in toxicological and transplantation studies.
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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".