Atlas of dihydrotestosterone actions on the transcriptome of prostate in vivo
Bibliographic record
Abstract
BACKGROUND: Using serial analysis of gene expression (SAGE), we studied the transcriptomic changes in vivo by dihydrotestosterone (DHT) treatment in mice to better understand androgen effects in the prostate. METHODS: Approximately 872,000 SAGE tags were isolated from intact and castrated (GDX) mice with and without DHT injection. RESULTS: GDX significantly altered 431 transcripts, including 110 transcripts restored by DHT, and 146 potentially new transcripts. Totally, 187 transcripts were significantly affected by DHT treatment, of which 124 were induced and 63 were repressed. Interestingly and consistent with the prostate's secretory role, DHT up-regulated the expression of many genes involved in various steps of protein metabolism such as synthesis, folding, and secretion. GDX modulated the expression of genes which induce cell apoptosis and inhibit cell proliferation through polyamine biosynthesis, retinoid X receptor actions as well as several signaling pathways and some related factors. These results clarify DHT effects on prostate transcriptome in the areas of protein metabolism, cell proliferation and apoptosis. In addition, we detected gene expression changes in metabolic pathways, cytoskeleton, immunity and endoplasmic reticulum stress. Furthermore, knockdown of S-adenosylmethionine decarboxylase 1 in LNCaP cells confirmed the importance of androgen-regulated genes (ARGs) in prostate cancer cell growth. CONCLUSION: Our data support the idea that ARGs are essential for the normal development of the prostate and can also be responsible for the pathogenesis of the prostate cancer.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".