Tetrahydrogestrinone induces a genomic signature typical of a potent anabolic steroid
Bibliographic record
Abstract
Tetrahydrogestrinone (THG) is a recently identified compound having the greatest impact in the world of sports. In order to obtain a highly accurate and sensitive assessment of the potential anabolic/androgenic activity of THG, we have used microarrays to identify its effect on the expression of practically all the 30,000 genes in the mouse genome and compared it with the effect of dihydrotestosterone (DHT), the most potent natural androgen. Quite remarkably, we found that 671 of the genes modulated by THG in the mouse muscle levator ani are modulated in a similar fashion by DHT, while in the gastrocnemius muscle and prostate, 95 and 939 genes respectively, are modulated in common by the two steroids. On the other hand, THG is more potent than DHT in binding to the androgen receptor, while, under in vivo conditions, THG possesses 20% of the potency of DHT in stimulating prostate, seminal vesicle and levator ani muscle weight in the mouse. The present microarray data provide an extremely precise and unquestionable signature of the androgenic/anabolic activity of THG, an approach which should apply to the analysis of the activity of any anabolic steroid.
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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".