Human Milk Oligosaccharides Increase Mucin Expression in Experimental Necrotizing Enterocolitis
Bibliographic record
Abstract
SCOPE: Necrotizing enterocolitis (NEC) is a leading cause of morbidity and death in preterm infants, occurring more often in formula-fed than breastfed infants. Studies in both rats and humans show that human milk oligosaccharides (HMOs) lower the incidence of NEC, but the mechanism underlying such protection is currently unclear. METHODS AND RESULTS: By extracting HMOs from pooled human breastmilk, the impact of HMOs on the intestinal mucin levels in a murine model of NEC are investigated. To confirm the results, the findings are validated by exposing human intestinal epithelial cells and intestinal organoids to HMOs and evaluated for mucin expression. HMO-gavage to pups increases Muc2 levels and decreases intestinal permeability to macromolecular dextran. HMO-treated cells have increased Muc2 expression, decreased bacterial attachment and dextran permeability during challenge by enteric pathogens. To identify the mediators involved in HMO induction of mucins, it is demonstrated that HMOs directly induce the expression of chaperone proteins including protein disulfide isomerase (PDI). Suppression of PDI activity removes the protective effects of HMOs on barrier function in vitro as well as NEC protection in vivo. CONCLUSIONS: Taken together, the results provide insights to the possible mechanisms by which HMOs protect the neonatal intestine through upregulation of mucins.
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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) | 0.002 | 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".