Current progress, challenges, and future prospects of testis organoids†
Bibliographic record
Abstract
Spermatogenic failure is believed to be a major cause of male infertility. The establishment of a testis organoid model would facilitate the study of such pathological mechanisms and open the possibility of male fertility preservation. Because of the complex structures and cellular events occurring within the testis, the establishment of a compartmentalized testis organoid with a complete spermatogenic cycle remains a challenge in all species. Since the late 20th century, a great variety of scaffold-based and scaffold-free testis cell culture systems have been established to recapitulate de novo testis organogenesis and in vitro spermatogenesis. The utilization of the hydrogel scaffolds provides a 3D microenvironment for testis cell growth and development, facilitating the reconstruction of de novo testis tissue-like structures and spermatogenic differentiation. Using a combination of different strategies, including the use of various scaffolding biomaterials, the incorporation of the living cells with high self-assembling capacity, and the integration of the advanced fabrication techniques, a scaffold-based testis organoid with a compartmentalized structure that supports in vitro spermatogenesis may be achieved. This article briefly reviews the current progress in the development of scaffold-based testis organoids while focusing on the scaffolding biomaterials (hydrogels), cell sources, and scaffolding approaches. Key challenges in current organoid studies are also discussed along with recommendations for future research.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".