Cell Type-Specific Remodelling of the Rat Hippocampus by Parity and Age
Bibliographic record
Abstract
Abstract Background The hippocampus undergoes extensive cellular remodelling throughout life. Parity, the experience of pregnancy and motherhood, triggers profound hormonal changes which modulate brain plasticity in the short and long term. Signatures of past parity are seen in the middle-aged hippocampus in humans and rodents, but how parity shapes cellular composition long-term after pregnancy have not been systematically examined using quantitative, cell-type-specific approaches. Methods We performed cell type deconvolution on bulk RNA-sequencing data from female rat hippocampus, comparing nulliparous and parous females across age (7 or 13 months either 30 days or 7 months after parturition). We harmonized 349 cell type annotations from three single-cell reference datasets into 27 biologically coherent categories using female-only data. Three-way ANOVA identified independent and interactive effects, while complementary analyses (random forest, PCA, DESeq2) identified parity-associated transcriptional signatures. Cell-specific functional enrichment employed weighted gene set meta-analysis across multiple pathway databases. Results Age emerged as the dominant factor, significantly altering six cell types, particularly somatostatin (SST) and parvalbumin/Vip interneurons. Regional effects (dorsal and ventral hippocampus) affected nine cell types, while age x region interactions identified two cell types. Parity independently affected three populations: dorsal CA3 pyramidal neurons, SST interneurons, and astrocytes. Cell-type-specific pathway analysis revealed distinct mechanisms including protein degradation in CA3 neurons, stress-response regulation in astrocytes, and disrupted GPCR/signalling-receptor programs in SST interneurons. Conclusions Our study shows that parity selectively remodels hippocampal cellular architecture through distinct, cell-type-specific molecular programs operating independently of age and region, establishing parity as a critical biological variable in aging research.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".