Breast Feeding and Melatonin: Implications for Improving Perinatal Health
Bibliographic record
Abstract
The biological underpinnings that drive the plethora of breastfeeding benefits over formula-feeding is an area of intense research, given the cognitive and emotional benefits as well as the offsetting of many childhood- and adult-onset medical conditions that breast-feeding provides. In this article, we review the research on the role of melatonin in driving some of these breastfeeding benefits. Melatonin is a powerful antioxidant, anti-inflammatory and antinociceptive as well as optimizing mitochondrial function. Melatonin is produced by the placenta and, upon parturition, maternal melatonin is passed to the infant upon breastfeeding with higher levels in night-time breast milk. As such, some of the benefits of breastfeeding may be mediated by the higher levels of maternal circulating night-time melatonin, allowing for circadian and antioxidant effects, as well as promoting the immune and mitochondrial regulatory aspects of melatonin; these actions may positively modulate infant development. Herein, it is proposed that some of the benefits of breastfeeding may be mediated by melatonin's regulation of the infant's gut microbiota and immune responses. As such, melatonin is likely to contribute to the early developmental processes that affect the susceptibility to a range of adult onset conditions. Early research on animal models has shown promising results for the regulatory role of melatonin.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".