The role of interindividual licking received and dopamine genotype on later‐life licking provisioning in female rat offspring
Bibliographic record
Abstract
INTRODUCTION: Rat mothers exhibit natural variations in care that propagate between generations of female offspring. However, there is limited information on genetic variation that could influence this propagation. METHODS: We assessed early-life maternal care received by individual female rat offspring, later-life maternal care provisioning, and dopaminergic activity in the maternal brain in relation to naturally occurring genetic polymorphisms linked to the dopaminergic system. We also conducted a systematic analysis of other genetic variants potentially related to maternal behavior in our Long-Evans rat population. RESULTS: While we did not find a direct relationship between early-life licking received and later-life licking provisioning, this relationship was indirectly affected by dopamine levels in the nucleus accumbens and dependent on variation in the dopamine receptor 2 gene (rs107017253). More specifically, female rat offspring with the A/G genotype showed a positive relationship between average licking received and dopamine levels in the nucleus accumbens of the maternal brain; there was no relationship with female rat offspring with the A/A genotype. The higher dopamine levels in the nucleus accumbens corresponded with higher maternal licking provisioning from postnatal days 2-9. We also discovered and validated several new variants that were predicted by our systematic analysis. CONCLUSION: Our findings suggest that genetic variation influences the relationship between early-life maternal care received and the dopaminergic system of the maternal brain, which can indirectly influence later-life maternal care provisioning.
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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 | 0.000 |
| 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".