A Novel Organoid Model of In Vitro Spermatogenesis Using Human Induced Pluripotent Stem Cells
Bibliographic record
Abstract
Abstract Infertility is thought to be caused by genetic mutations and dysfunction in the cellular niche where spermatogenesis takes place. An understanding of the specialized cellular processes which drive spermatogenesis is needed to develop treatments; however, the development of in vitro systems to study these cells has been hindered by our reliance on rarely available human testicular tissues for research. Human induced pluripotent stem cells (hiPSCs) can be used to derive human testicular-like cells, and thus provide an avenue for the development of in vitro testicular model systems. Therefore, this study set out to engineer a human testicular tissue model using hiPSCs for the first time. We demonstrate the ability of hiPSC-derived testicular cells to self-organize and mature into testicular-like tissues using organoid culture. Moreover, we show that hiPSC-derived testicular organoids promote testicular somatic cell maturation and spermatogenesis up to the post-meiotic spermatid stage. These hiPSC-derived testicular organoids have the potential to replace rarely available primary testicular tissues to further infertility research in an in vitro setting.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".