Associations of maternal inflammatory states with human milk composition in mothers of preterm infants
Bibliographic record
Abstract
Introduction: Overweight/obesity (ow/ob) is increasing in prevalence in pregnant women, and it is associated with other pro-inflammatory states, such as pre-eclampsia, gestational diabetes, and preterm labor. Data are lacking if mothers experiencing inflammatory states who deliver preterm have mother's own milk (MOM) with differing inflammatory markers or pro-inflammatory fatty acid (FA) profiles. Methods: The aim was to explore associations of maternal pre- and perinatal inflammatory states with levels of inflammatory markers and/or FAs in longitudinal samples of MOM from mothers of preterm infants born <1,250 g. Inflammatory states included pre-pregnancy ow/ob, diabetes, chorioamnionitis (chorio), preterm labor (PTL), premature rupture of membranes (PROM), pre-eclampsia, and cesarian delivery. In MOM, inflammatory markers studied included c-reactive protein (CRP), free choline, IFN-Ɣ, IL-10, IL-1β, IL-1ra, IL-6, IL-8, and TNF-α, and FAs included omega-6:omega-3 ratio, arachidonic acid, docosahexaenoic acid, linoleic acid, monounsaturated FAs, and saturated FAs. The above inflammatory states were assessed individually, and the healthiest mothers (normal BMI, no chorio, and ± no pre-eclampsia) were grouped. Regression analysis tested associations at baseline (day 5) and over time using generalized estimating equations. Results: < 0.05) than others. MOM IL-8 levels were lower with chorio and PTL at baseline. No significant associations were found for other individual or grouped inflammatory states nor for other MOM inflammatory markers nor FA profiles at baseline. Discussion: In conclusion, MOM CRP levels are positively associated with inflammatory states, such as ow/ob. Reassuringly, there was no association between FA profiles or most other inflammatory markers and maternal inflammatory states. Further studies are needed to determine potential associations or ramifications of MOM CRP in vulnerable preterm infants.
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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) | 0.000 | 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".