Exploring the Complex Pathophysiology of Necrotizing Enterocolitis in Preterm Neonates
Bibliographic record
Abstract
Necrotizing enterocolitis (NEC) is the most common gastrointestinal emergency in preterm neonates, with a mortality rate of 30-50% in advanced cases. Despite decades of research, its multifactorial pathophysiology remains incompletely understood. This review summarizes recent advances in NEC research and proposes an integrative theoretical framework for its pathogenesis. We examine key contributing factors, including intestinal vascular development, mucosal immunity, intestinal regeneration, the enteric nervous system, and the gut microbiome, highlighting how prematurity disrupts these processes and predisposes neonates to NEC. Furthermore, we propose a sequential model of NEC pathogenesis, hypothesizing that impaired intestinal microcirculation in preterm neonates compromises blood flow in response to enteral feeding, leading to localized ischemia. This initiates epithelial barrier dysfunction, exacerbates inflammatory responses, impairs intestinal regeneration, and disrupts enteric nervous system function, collectively driving NEC progression. By integrating experimental and clinical findings, we provide a comprehensive perspective on NEC initiation in preterm neonates and identify potential avenues for future research and therapeutic interventions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".