Different Forms of Oestrogen Rapidly Upregulate Cell Proliferation in the Dentate Gyrus of Adult Female Rats
Bibliographic record
Abstract
Oestrogens are known to exert significant structural and functional effects in the hippocampus of adult rodents. The dentate gyrus of the hippocampus retains the ability to produce neurones throughout adulthood and 17beta-oestradiol has been shown to influence hippocampal neurogenesis in adult female rats. The effects of other oestrogens, such as oestrone and 17alpha-oestradiol, on neurogenesis have not been investigated. The present study aimed to investigate the effects of 17beta-oestradiol, oestradiol benzoate, oestrone, and 17alpha-oestradiol on cell proliferation in ovariectomised adult female rats at two different time points. Young ovariectomised female rats were injected with one of the oestrogens at one of three doses. In Experiment 1, rats were exposed to the hormone for 4 h and, in Experiment 2, rats were exposed to the hormone for 30 min prior to 5-bromo-2-deoxyuridine injection to label proliferating cells and their progeny. We found that young ovariectomised females responded with increased cell proliferation to most oestrogens, except oestradiol benzoate, after 30 min of exposure. However, administration of oestrogens for a longer time interval was ineffective at increasing cell proliferation. After 30 min, 17beta-oestradiol and oestrone increased cell proliferation at low (0.3 microg) and high (10 microg) doses, whereas 17alpha-oestradiol increased cell proliferation at medium (1 microg) and high doses. The results of the present study indicate that different oestrogens rapidly increase cell proliferation in a dose-dependent manner, possibly through a nonclassical, nongenomic mechanism. Future experiments should focus on further elucidating the specific pathways utilised by each oestrogen. These results have important therapeutic implications because it may be possible to use 17alpha-oestradiol and lower doses of oestrogens in hormone replacement therapies.
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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 | 0.001 | 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) | 0.002 | 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".