Dynamic changes in the expression of apoptosis-related genes in differentiating gonocytes and in seminomas
Bibliographic record
Abstract
Apoptosis is an integral part of the spermatogenic process, necessary to maintain a proper ratio of Sertoli to germ cell numbers and provide an adequate microenvironment to germ cells. Apoptosis may also represent a protective mechanism mediating the elimination of abnormal germ cells. Extensive apoptosis occurs between the first and second postnatal weeks, at the point when gonocytes, precursors of spermatogonial stem cells, should have migrated toward the basement membrane of the tubules and differentiated into spermatogonia. The mechanisms regulating this process are not well-understood. Gonocytes undergo phases of proliferation, migration, and differentiation which occur in a timely and closely regulated manner. Gonocytes failing to migrate and differentiate properly undergo apoptosis. Inadequate gonocyte differentiation has been suggested to lead to testicular germ cell tumor (TGCT) formation. Here, we examined the expression levels of apoptosis-related genes during gonocyte differentiation by quantitative real-time polymerase chain reaction, identifying 48 pro- and anti-apoptotic genes increased by at least two-fold in rat gonocytes induced to differentiate by retinoic acid, when compared to untreated gonocytes. Further analysis of the most highly expressed genes identified the pro-apoptotic genes Gadd45a and Cycs as upregulated in differentiating gonocytes and in spermatogonia compared with gonocytes. These genes were also significantly downregulated in seminomas, the most common type of TGCT, compared with normal human testicular tissues. These results indicate that apoptosis-related genes are actively regulated during gonocyte differentiation. Moreover, the down-regulation of pro-apoptotic genes in seminomas suggests that they could represent new therapeutic targets in the treatment of TGCTs.
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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 | 0.001 | 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".