Ablation of proliferating neural stem cells during early life is sufficient to reduce adult hippocampal neurogenesis
Bibliographic record
Abstract
Environmental exposures during early life, but not during adolescence or adulthood, lead to persistent reductions in neurogenesis in the adult hippocampal dentate gyrus (DG). The mechanisms by which early life exposures lead to long-term deficits in neurogenesis remain unclear. Here, we investigated whether targeted ablation of dividing neural stem cells during early life is sufficient to produce long-term decreases in DG neurogenesis. Having previously found that the stem cell lineage is resistant to long-term effects of transient ablation of dividing stem cells during adolescence or adulthood (Kirshenbaum, Lieberman, Briner, Leonardo, & Dranovsky, ), we used a similar pharmacogenetic approach to target dividing neural stem cells for elimination during early life periods sensitive to environmental insults. We then assessed the Nestin stem cell lineage in adulthood. We found that the adult neural stem cell reservoir was depleted following ablation during the first postnatal week, when stem cells were highly proliferative, but not during the third postnatal week, when stem cells were more quiescent. Remarkably, ablating proliferating stem cells during either the first or third postnatal week led to reduced adult neurogenesis out of proportion to the changes in the stem cell pool, indicating a disruption of the stem cell function or niche following stem cell ablation in early life. These results highlight the first three postnatal weeks as a series of sensitive periods during which elimination of dividing stem cells leads to lasting alterations in adult DG neurogenesis and stem cell function. These findings contribute to our understanding of the relationship between DG development and adult neurogenesis, as well as suggest a possible mechanism by which early life experiences may lead to lasting deficits in adult hippocampal neurogenesis.
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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 | 0.001 |
| 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".