Long-lasting effects of transient, perinatal fluoxetine exposure on cell proliferation in the dentate gyrus of mice
Bibliographic record
Abstract
Abstract In the adult mammalian brain, up-regulation of serotonin via the selective serotonin reuptake inhibitor fluoxetine increases hippocampal neurogenesis. However, research assessing the long-term effects of modulating serotonin during the developmental period on hippocampal neurogenesis, is sparse. Here we evaluated hippocampal neurogenesis early (postnatal day 12), and later in life (postnatal day 60), in the offspring of mouse dams that were administered fluoxetine in their drinking water from embryonic day 15 (E15) through postnatal day 12 (P12). Fluoxetine-exposed mice had significantly higher levels of neuronal proliferation at P12, and P60, despite cessation of fluoxetine on P12. These effects were limited to proliferation, as survival of postnatal-born hippocampal neurons was unaltered. Mice exposed to fluoxetine also showed significantly higher levels of cell death, suggesting that homeostatic mechanisms present within the hippocampus may limit integration of adult-born neurons into the existing neuronal network. These findings demonstrate modulation of serotonin during development may be sufficient to induce long-lasting changes in hippocampal neurogenesis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".