TAp73 is required for spermatogenesis and the maintenance of male fertility
Bibliographic record
Abstract
The generation of viable sperm proceeds through a series of coordinated steps, including germ cell self-renewal, meiotic recombination, and terminal differentiation into functional spermatozoa. The p53 family of transcription factors, including p53, p63, and p73, are critical for many physiological processes, including female fertility, but little is known about their functions in spermatogenesis. Here, we report that deficiency of the TAp73 isoform, but not p53 or ΔNp73, results in male infertility because of severe impairment of spermatogenesis. Mice lacking TAp73 exhibited increased DNA damage and cell death in spermatogonia, disorganized apical ectoplasmic specialization, malformed spermatids, and marked hyperspermia. We demonstrated that TAp73 regulates the mRNA levels of crucial genes involved in germ stem/progenitor cells (CDKN2B), spermatid maturation/spermiogenesis (metalloproteinase and serine proteinase inhibitors), and steroidogenesis (CYP21A2 and progesterone receptor). These alterations of testicular histology and gene expression patterns were specific to TAp73 null mice and not features of mice lacking p53. Our work provides previously unidentified in vivo evidence that TAp73 has a unique role in spermatogenesis that ensures the maintenance of mitotic cells and normal spermiogenesis. These results may have implications for the diagnosis and management of human male infertility.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".