Milk consumption and the prepubertal somatotropic axis
Bibliographic record
Abstract
BACKGROUND: Nutrients, hormones and growth factors in dairy foods may stimulate growth hormone (GH), insulin-like growth factor I (IGF-I), and raise the ratio of IGF-I to its binding protein, IGFBP-3. We conducted pilot studies in Mongolia and Massachusetts to test the extent to which milk intake raised somatotropic hormone concentrations in prepubertal children. METHODS: In Ulaanbaatar, we compared plasma levels before and after introducing 710 ml daily whole milk for a month among 46 10-11 year old schoolchildren. In a randomized cross-over study in Boston, we compared plasma hormone levels of 28 6-8 year old girls after one week of drinking 710 ml low fat (2%) milk with their hormone levels after one week of consuming a macronutrient substitute for milk. RESULTS: After a month of drinking whole milk, Mongolian children had higher mean plasma levels of IGF-I (p < 0.0001), IGF-I/IGFBP-3 (p < 0.0001), and 75th percentile of GH levels (p = 0.005). After a week of drinking low fat milk, Boston girls had small and non-significant increases in IGF-1, IGF-1/IGFBP-3 and GH. CONCLUSION: Milk drinking may cause increases in somatotropic hormone levels of prepubertal girls and boys. The finding that milk intake may raise GH levels is novel, and suggests that nutrients or bioactive factors in milk may stimulate endogenous GH production.
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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".