Drug Ligand-Induced Activation of Translocator Protein (TSPO) Stimulates Steroid Production by Aged Brown Norway Rat Leydig Cells
Bibliographic record
Abstract
Translocator protein (TSPO; 18 kDA) is a high-affinity cholesterol-binding protein that is integrally involved in cholesterol transfer from intracellular stores into mitochondria, the rate-determining step in steroid formation. Previous studies have shown that TSPO drug ligands are able to activate steroid production by MA-10 mouse Leydig tumor cells and by mitochondria isolated from steroidogenic cells. We hypothesized herein that the direct, pharmacological activation of TSPO might induce aged Leydig cells, which are characterized by reduced T production, to produce significantly higher levels of T both in vitro and in vivo. To test this, we first examined the in vitro effects of the TSPO selective and structurally distinct drug ligands N,N-dihexyl-2-(4-fluorophenyl)indole-3-acetamide (FGIN-1-27) and benzodiazepine 4'-chlorodiazepam (Ro5-4864) on steroidogenesis by Leydig cells isolated from aged (21-24 months old) and young adult (3-6 months old) Brown Norway rats. The ligands stimulated Leydig cell T production significantly, and equivalently, in cells of both ages, an effect that was significantly inhibited by the specific TSPO inhibitor 5-androsten-3,17,19-triol (19-Atriol). Additionally, we examined the in vivo effects of administering FGIN-1-27 to young and aged rats. In both cases, serum T levels increased significantly, consistent with the in vitro results. Indeed, serum T levels in aged rats administered FGIN-1-27 were equivalent to T levels in the serum of control young rats. Taken together, these results indicate that although there are reduced amounts of TSPO in aged Leydig cells, its direct activation is able to increase T production. We suggest that this approach might serve as a therapeutic means to increase steroid levels in vivo in cases of primary hypogonadism.
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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".