Mother to infant or infant to mother? Reciprocal regulation of responsiveness to stress in rodents and the implications for humans
Bibliographic record
Abstract
Optimal early development in most species is dependent upon a stable relationship between the mother and her infant. The research described here focuses on the reciprocal nature of this dyad in rodents and humans, with respect to the regulation of responsiveness to stress in both mother and offspring. Dietary influences are critical not only to regulate infant growth but also to modulate the response of the neuroendocrine system to stress and, possibly, to influence some aspects of brain development. In particular, we discuss the role of leptin, a protein produced in the adipose tissue and present in maternal milk, that reduces responses to stress in the infant. We suggest that leptin acts on both central (hypothalamus and hippocampus) and peripheral (pituitary, adrenal gland) targets in the infant to reduce exposure to glucocorticoids and enhance hippocampal development during a sensitive period of brain development. There is also evidence to support the reverse regulatory influence, in which maternal state is profoundly affected by stimulation from the young. During the period of lactation, mothers exhibit lower neuroendocrine and behavioural responses to several types of stressors, except possibly those representing a threat to the infant. This ability to "filter" relevant from irrelevant stimuli while caring for their young might be viewed as adaptive for the mother-infant dyad, and the inability to filter adequately stressful stimuli could at least in part be associated with the development of postpartum depression.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".