Early and Late Effects of Maternal Experience on Hippocampal Neurogenesis, Microglia, and the Circulating Cytokine Milieu
Bibliographic record
Abstract
Abstract The maternal brain displays considerable plasticity, and motherhood is associated with changes in affective and cognitive function. Motherhood can alter the trajectory of brain ageing, including modifications to neuroplasticity and cognition. Here, we investigated the short- and long-term effects of motherhood on hippocampal neurogenesis, microglial density and morphology, and circulating cytokines, domains known to be altered with age and implicated in cognition and mood. Female rats were bred then euthanized during gestation or at various postpartum timepoints, culminating in middle age, and nulliparous rats served as age-matched controls. Hippocampal neurogenesis was significantly suppressed during gestation and the postpartum period. Interestingly, neurogenesis declined significantly in middle-aged nulliparous rats, but increased in primiparous rats across the same period. Transient postpartum adaptations to the neuroimmune environment of the hippocampus were evidenced, as Iba-1-immunoreactive microglia assumed a de-ramified morphology followed by increased density. Intriguingly, ageing-related changes in circulating cytokines were dependent on parity. These adaptations in neurogenic and immune processes may have ramifications for maternal mood and cognition across the peripartum period and beyond.
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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".