Treatment of necrotizing enterocolitis by conditioned medium derived from human amniotic fluid stem cells
Bibliographic record
Abstract
PURPOSE: Necrotizing enterocolitis (NEC) is one of the most distressing gastrointestinal emergencies affecting neonates. Amniotic fluid stem cells (AFSC) improve intestinal injury and survival in experimental NEC but are difficult to administer. In this study, we evaluated whether conditioned medium (CM) derived from human AFSC have protective effects. METHODS: Three groups of C57BL/6 mice were studied: (i) breast-fed mice as control; (ii) experimental NEC mice receiving PBS; and (iii) experimental NEC mice receiving CM. NEC was induced between post-natal days P5 through P9 via: (A) gavage feeding of hyperosmolar formula four-time a day; (B) 10 minutes hypoxia prior to feeds; and (C) lipopolysaccharide administration on P6 and P7. Intra-peritoneal injections of either PBS or CM were given on P6 and P7. All mice were sacrificed on P9 and terminal ileum were harvested for analyses. RESULTS: CM treatment increased survival and reduced intestinal damage, decreased mucosal inflammation (IL-6; TNF-α), neutrophil infiltration (MPO), and apoptosis (CC3), and also restored angiogenesis (VEGF) in the ileum. Additionally, CM treated mice had increased levels of epithelial proliferation (Ki67) and stem cell activity (Olfm4; Lgr5) compared to NEC+PBS mice, showing restored intestinal regeneration and recovery during NEC induction. CM proteomic analysis of CM content identified peptides that regulated immune and stem cell activity. CONCLUSIONS: CM derived from human AFSC administered in experimental NEC exhibited various benefits including reduced intestinal injury and inflammation, increased enterocyte proliferation, and restored intestinal stem cell activity. This study provides the scientific basis for the use of CM derived from AFSC in neonates with NEC.
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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".