Formation of organotypic testicular organoids in microwell culture†
Bibliographic record
Abstract
Three-dimensional (3D) organoids can serve as an in vitro platform to study cell-cell interactions, tissue development, and toxicology. Development of organoids with tissue architecture similar to testis in vivo has remained a challenge. Here, we present a microwell aggregation approach to establish multicellular 3D testicular organoids from pig, mouse, macaque, and human. The organoids consist of germ cells, Sertoli cells, Leydig cells, and peritubular myoid cells forming a distinct seminiferous epithelium and interstitial compartment separated by a basement membrane. Sertoli cells in the organoids express tight junction proteins claudin 11 and occludin. Germ cells in organoids showed an attenuated response to retinoic acid compared to germ cells in 2D culture indicating that the tissue architecture of the organoid modulates response to retinoic acid similar to in vivo. Germ cells maintaining physiological cell-cell interactions in organoids also had lower levels of autophagy indicating lower levels of cellular stress. When organoids were treated with mono(2-ethylhexyl) phthalate (MEHP), levels of germ cell autophagy increased in a dose-dependent manner, indicating the utility of the organoids for toxicity screening. Ablation of primary cilia on testicular somatic cells inhibited the formation of organoids demonstrating an application to screen for factors affecting testicular morphogenesis. Organoids can be generated from cryopreserved testis cells and preserved by vitrification. Taken together, the testicular organoid system recapitulates the 3D organization of the mammalian testis and provides an in vitro platform for studying germ cell function, testicular development, and drug toxicity in a cellular context representative of the testis in vivo.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".