Preservation and transplantation of porcine testis tissue
Bibliographic record
Abstract
Grafting of immature mammalian testis tissue to mouse hosts can preserve the male germline. To make this approach applicable to a clinical or field situation, it is imperative that the testis tissue and/or spermatozoa harvested from grafted tissue are preserved successfully. The aim of the present study was to evaluate protocols for the preservation of testis tissue in a porcine model. Testis tissue was stored at 4 degrees C for short-term preservation or cryopreserved by slow-freezing, automated slow-freezing or vitrification for long-term storage. Preserved tissue was transplanted ectopically to mouse hosts and recovered xenografts were analysed histologically. In addition, spermatozoa were harvested from xenografts and cryopreserved. Total cell viability and germ cell viability remained high after tissue preservation. Complete spermatogenesis occurred in xenografts preserved by cooling up to 48 h, whereas spermatogenesis progressed to round spermatids in the xenografts that were frozen-thawed before grafting. Approximately 50% of spermatozoa harvested from xenografts remained viable after freezing and thawing. The in vivo developmental potential of cryopreserved tissue was reduced despite high post-thaw viability. Therefore, it is important to evaluate germ cell differentiation in vivo in addition to cell viability in vitro when optimising freezing protocols for testis tissue.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".