Bovine milk-derived exosomes enhance goblet cell activity and prevent the development of experimental necrotizing enterocolitis
Bibliographic record
Abstract
Necrotizing enterocolitis (NEC) is characterized by intestinal injury and impaired mucin synthesis. We recently showed that breast milk exosomes from rodents promote intestinal cell viability, epithelial proliferation, and stem cell activity, but whether they also affect mucus production is unknown. Therefore, the aim of this study was to investigate the effects of bovine milk-derived exosomes on goblet cell expression in experimental NEC and delineate potential underlying mechanisms of action. Exosomes were isolated from bovine milk by ultracentrifugation and confirmed by Nanoparticle Tracking Analysis and through the detection of exosome membrane markers. To study the effect on mucin production, human colonic LS174T cells were cultured and exposed to exosomes. Compared to control, exosomes promoted goblet cell expression, as demonstrated by increased mucin production and relative expression levels of goblet cell expression markers trefoil factor 3 (TFF3) and mucin 2 (MUC2). In addition, exosome treatment enhanced the expression of glucose-regulated protein 94 (GRP94), the most abundant intraluminal endoplasmic reticulum (ER) chaperone protein that aids in protein synthesis. Furthermore, experimental NEC was induced in mouse pups by hyperosmolar formula feeding, lipopolysaccharide administration and hypoxia exposure on postnatal days 5-9. Milk exosomes were given with each gavage feed. NEC was associated with ileal morphological injury and reduction in MUC2+ goblet cells and GRP94+ cells per villus. Exosome administration to NEC pups prevented these changes. This research highlights the potential novel application of milk-derived exosomes in preventing the development of NEC in high-risk infants when breast milk is not available.
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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 | 0.001 |
| 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".