Puberty Blocker and Aging Impact on Testicular Cell States and Function
Bibliographic record
Abstract
Spermatogonial stem cell (SSC) acquisition of meiotogenetic state during puberty to produce genetically diverse gametes is blocked by drugs collectively referred as 'puberty blocker' (PB). Investigating the impact of PB on juvenile SSC state and function is challenging due to limited tissue access and clinical data. Herein, we report largest clinically annotated juvenile testicular biorepository with all children with gender dysphoria on chronic PB treatment highlighting shift in pediatric patient demography in US. At the tissue level, we report mild-to-severe sex gland atrophy in PB treated children. We developed most extensive integrated single-cell RNA dataset to date (>100K single cells; 25 patients), merging both public and novel (52 month PB-treated) datasets, alongside innovative computational approach tailed for germ cells and evaluated the impact of PB and aging on SSC. We report novel constitutional ranges for each testicular cell type across the entire age spectrum, distinct effects of treatments on prepubertal vs adult SSC, presence of spermatogenic epithelial cells exhibiting post-meiotic-state, irrespective of age, puberty status, or PB treatment. Further, we defined distinct effects of PB and aging on testicular cell lineage composition, and SSC meiotogenetic state and function. Using single cell data from prepubertal and young adult, we were able to accurately predict sexual maturity based both on overall cell type proportions, as well as on gene expression patterns within each major cell type. Applying these models to a PB-treated patient that they appeared pre-pubertal across the entire tissue. This combined with the noted gland atrophy and abnormalities from the histology data raise a potential concern regarding the complete 'reversibility' and reproductive fitness of SSC. The biorepository, data, and research approach presented in this study provide unique opportunity to explore the impact of PB on testicular reproductive health.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".