The Association between Maternal Oral Inflammation and Neutrophil Phenotypes and Poly-Unsaturated Fatty Acids Composition in Human Milk: A Prospective Cohort Study
Bibliographic record
Abstract
This prospective cohort study aimed to investigate the impact of maternal oral inflammation on human milk composition including neutrophil counts, activation state (based on cluster of differentiation (CD) markers expression), and fatty acid levels. Fifty mothers were recruited from St. Michael's hospital, Toronto, and followed up from 2-4 weeks until 4 months postpartum. Oral rinse and human milk samples were collected at both timepoints. Oral polymorphonuclear neutrophils (oPMNs) within the rinses were quantified using flow cytometry and the participants' oral health state was categorized into three groups (i.e., healthy, moderate, and severe) based on the oPMNs counts. Fatty acids were identified and quantified using a gas chromatography-flame ionization detector (GC-FID). Compared to mothers with a healthy oral health state, mothers with moderate to severe oral inflammation had a statistically significant decrease in the expression of CD64 biomarker, an increase in the expression of CD14 biomarker on human milk neutrophils and a decrease in the levels of eicosapentaenoic acid (C20:5n-3) in their human milk at follow-up compared to baseline. This study demonstrates for the first time that maternal oral inflammation can affect human milk composition. The mechanism by which these alterations can affect infant health outcomes in the long term critically needs to be considered.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 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) | 0.000 | 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 teacher head, 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".