Chronic aromatase inhibition increases ventral hippocampal neurogenesis in middle-aged female mice
Bibliographic record
Abstract
Abstract Letrozole, a third-generation aromatase inhibitor, prevents the production of estrogens in the final step in conversion from androgens. Due to its efficacy at suppressing estrogens, letrozole has recently taken favor as a first-line adjuvant treatment for hormone-responsive breast cancer in middle-aged women. Though patient response to letrozole has generally been positive, there is conflicting evidence surrounding its effects on the development of depression. It is possible that the potential adverse effects of letrozole on mood are a result of the impact of hormonal fluctuations on neurogenesis in the hippocampus. Thus, to clarify the effects of letrozole on the hippocampus and behavior, we examined how chronic administration affects hippocampal neurogenesis and depressive-like behavior in middle-aged, intact female mice. Mice were given either letrozole (1mg/kg) or vehicle by injection (i.p.) daily for 3 weeks. Depressive-like behavior was assessed during the last 3 days of treatment using the forced swim test, tail suspension test, and sucrose preference test. The production of new neurons was quantified using the immature neuronal marker doublecortin (DCX), and cell proliferation was quantified using the endogenous marker Ki67. We found that letrozole increased DCX and Ki67 expression and maturation in the dentate gyrus, but had no significant effect on depressive-like behavior. Our findings suggest that a reduction in estrogens in middle-aged females increases hippocampal neurogenesis without any adverse impact on depressive-like behavior; as such, this furthers our understanding of how estrogens modulate neurogenesis, and to the rationale for the utilization of letrozole in the clinical management of breast cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".