Human milk extracellular vesicles modulate inflammation and cell survival in intestinal and immune cells
Bibliographic record
Abstract
Human milk contains extracellular vesicles (EVs) that carry bioactive molecules such as microRNA, to the newborn intestine. The downstream effects of EV cargo on signaling and immune modulation may shield neonates against inflammatory diseases, including necrotizing enterocolitis. Premature infants are especially at risk, while human milk-feeding may offer protection. The effect of gestational-age specific term and preterm EVs from transitional human milk was characterized on human intestinal epithelial cells (HIECs and Caco-2), primary macrophages, and THP-1 monocytes. We hypothesized that term and preterm EVs differentially influence immune-related cytokines and cell death. We found that preterm EVs were enriched in CD14 surface marker, while both term and preterm EVs increased epidermal growth factor secretion. Following inflammatory stimuli, only term EVs inhibited secretion of IL-6 in HIECs, and reduced expression of pro-inflammatory cytokine IL-1β in macrophages. Term and preterm EVs inhibited secretion of IL-1β and reduced inflammasome related cell death. We proposed that human milk EVs regulate immune-related signaling via their conserved microRNA cargo, which could promote tolerance and a homeostatic immune response. These findings provide basis for further studies into potential therapeutic supplementation with EVs in vulnerable newborn populations by considering functional, gestational age-specific effects. IMPACT: This study reveals distinct functional differences between term and preterm transitional human milk extracellular vesicles (EVs) highlighting the importance of gestational age in their bioactivity. Term EVs uniquely inhibited IL-6 secretion, IL-1β expression, and apoptosis following inflammatory stimuli. Both term and preterm human milk EVs reduced IL-1β secretion and inflammasome-induced cell death. Conserved human milk extracellular vesicle microRNA cargo could be a mediator of the anti-inflammatory effects, particularly targeting cytokine production, the inflammasome, and programmed cell death. These findings underscore the importance of considering gestational age in future research exploring the therapeutic potential of human milk extracellular vesicles to prevent or treat intestinal inflammatory diseases in neonates.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".