The human milk endocannabinoidome and neonatal growth in gestational diabetes
Bibliographic record
Abstract
Objective: to gestational diabetes mellitus (GDM) are more likely to develop obesity. The objective of this cross-sectional study is to compare the profile of eCBome mediators in milk of women with gestational diabetes (GDM+) and without (GDM-) and to assess the association with offspring growth. The hypothesis is that the eCBome of GDM+ human milk is altered and associated with a difference in infant growth. Methods: Circulating eCBome mediators were measured by LC-MS/MS in human milk obtained at 2 months postpartum from GDM+ (n=24) and GDM- (n=29) women. Infant weight and height at 2 months were obtained from the child health record. Z-scores were calculated. Results: Circulating Npalmitoylethanolamine (PEA) was higher in human milk of GDM+ women than in GDM- women (4.9 ± 3.2 vs. 3.3 ± 1.7, p=0.04). Higher levels were also found for several 2monoacyl-glycerols (2-MAGs) (p<0.05). The levels of NAEs (β=-4.6, p=0.04) and especially non-omega-3 NAEs (B=-5.6, p=0.004) in human milk were negatively correlated with weight-for-age z-score of GDM+ offspring. Conclusion: The profile of eCBome mediators in human milk at 2 months postpartum was different in GDM+ compared to GDM- women and was associated with GDM+ offspring growth at 2 months. Clinical trial registration: ClinicalTrials.gov, identifier (NCT04263675 and NCT02872402).
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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 | 0.001 |
| 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 | 0.000 |
| 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".