The Application of Biomarkers of Spermatogonial Stem Cells for Restoring Male Fertility
Bibliographic record
Abstract
Spermatogonial stem cells (SSCs) are defined by their ability to both self-renew and produce differentiated germ cells that will develop into functional spermatozoa. Because of this ability, SSCs can reestablish spermatogenesis after testicular damage caused by cytotoxic agents or after transplantation into an infertile recipient. Therefore, SSCs are an important target cell for restoring male fertility, particularly for cancer patients who have to undergo sterilizing cancer therapies. In the mouse, the identification of SSC markers allows for the isolation of a highly enriched population of stem cells. This enriched stem cell population can be expanded in culture for an indefinite period of time, cryopreserved, and transplanted into infertile recipients to restore fertility. Thus, the identification of markers and the establishment of a long-term culture system for human SSCs will be crucial for realizing the potential of these cells in a clinical setting. In this article, we focus on the markers that have been identified for mouse SSCs and discuss how human SSC markers may be used in the restoration of fertility.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".