The Number of Grafted Fragments Affects the Outcome of Testis Tissue Xenografting from Piglets into Recipient Mice
Bibliographic record
Abstract
To optimize the procedure for testis tissue xenografting, we grafted 2, 4, 8, or 16 small fragments of immature porcine testis tissue under the back skin of immunodeficient castrated mice (n = 10 mice/group). At 8 months post grafting, the graft recovery rate did not differ between groups; however, not only the total but also the average graft weights were higher (by approximately 12-fold and approximately 2.5-fold, resp.) in mice receiving 16 fragments than those receiving 2 fragments (P < .05). The recipient mice with 16 fragments had the largest vesicular glands (indicators of testosterone release by the grafts) compared with those with 2 fragments (P = .007). The grafts in the group of 16 fragments also had more (P < .05) percentage of tubules with round spermatids than those of the group of mice receiving 2 fragments. Therefore, recipient mice can be grafted with at least 16 testis tissue fragments for optimal results.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".