Neural androgen receptors affect the number of surviving new neurones in the adult dentate gyrus of male mice
Bibliographic record
Abstract
Adult hippocampal neurogenesis occurs in many mammalian species. In rats, the survival of new neurones within the hippocampus is modulated by the action of androgen via the androgen receptor (AR); however, it is not known whether this holds true in mice. Furthermore, the evidence is mixed regarding whether androgens act in neural tissue or via peripheral non-neural targets to promote new neurone survival in the hippocampus. We evaluated whether the action of androgen via AR underlies the survival of new neurones in mice, and investigated whether increasing AR selectively in neural tissue would increase new neurone survival in the hippocampus. We used the cre-loxP system to overexpress AR only in neural tissues (Nestin-AR). These males were compared with wild-type males, as well as control males with 1 of the 2 mutations required for overexpression. Mice were gonadectomised and injected with the DNA synthesis marker, bromodeoxyuridine (BrdU) and for 37 days (following BrdU injection), mice were treated with oil or dihydrotestosterone (DHT). Using immunohistochemistry, proliferation (Ki67) and survival (BrdU) of new neurones were both evaluated in the dorsal and ventral dentate gyrus. Dihydrotestosterone treatment increased the survival of new neurones in the entire hippocampus in wild-type mice and control mice that only have 1 of 2 necessary mutations for transgenic expression. However, DHT treatment did not increase the survival of new neurones in mice that overexpressed AR in neural tissue. Cell proliferation (Ki67) and cell death (pyknotic cells) were not affected by DHT treatment in wild-type or transgenic males. These results suggest that androgens act via neural AR to affect hippocampal neurogenesis by promoting cell survival; however, the relationship between androgen dose and new neurone survival is nonlinear.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".