Effect of resource availability on biparental care, and offspring neural and behavioral development in the California mouse (<i>Peromyscus californicus</i>)
Bibliographic record
Abstract
Maternal care influences cognitive function in humans, primates and rodents; however, little is known about the effect of biparental care. Environmental factors such as resource availability play an important role in modulating parental investment strategies with subsequent effects on the offspring. Thus, we examined the interaction between foraging demand and biparental care on hippocampal development and novel object recognition in the monogamous, biparental California mouse. We characterized biparental behavior for 15 days in families exposed to either control (ad libitum feeding) or a high-foraging demand across the weaning period. Adult male offspring were then tested in the open field, and for novel object and place recognition, as well as for hippocampal synaptic density and the expression of genes encoding for subunits of the N-methyl-D-aspartate (NMDA) receptor complex, and the postsynaptic density (PSD)-95 scaffolding protein. Under high-foraging demand, the mothers' body weight was decreased at weaning and fathers spent significantly less time in contact with pups. Offspring reared under high-foraging demand weighed less at weaning and, as adults, were more fearful in the open field and showed profound deficits in both novel object and place recognition. While synaptic density and NR1 mRNA expression were unaffected, offspring reared under high-foraging demand showed increased NR2A and decreased NR2B mRNA expression. Further, PSD-95 protein expression was decreased in mice reared under high-foraging demand. Together, the results suggest that resource availability affects biparental investment strategies, with subsequent effects on hippocampal development and novel object recognition in the offspring.
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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) | 0.001 | 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) | 0.001 | 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".