Stem cells as a potential therapy for necrotizing enterocolitis
Bibliographic record
Abstract
INTRODUCTION: Necrotizing enterocolitis (NEC) is a severe gastrointestinal disease of neonates, especially those born prematurely, that remains an important cause of morbidity and mortality. Although current treatments such as inotropes, antibiotics and ventilation are supportive, there is an urgent need for novel therapies that specifically target the affected intestine. AREAS COVERED: We briefly introduce the disease and the effects on intestinal epithelia. We provide a brief description of amniotic fluid stem (AFS) cells, and then describe some recent data in which AFS cells were beneficial in an animal model of NEC and a potential mechanism is described. The effects of AFS cells are compared with data on bone marrow mesenchymal stem cells. The potential implications of these findings for therapy are discussed. EXPERT OPINION: The current data are promising and demonstrate that stem cells do have an effect in rodent models of NEC. However, the short timescale, limited ability for longitudinal evaluation and uncertain clinical relevance of these models means that there are considerable challenges to be overcome before attempting stem cell therapy in clinical trials. Nevertheless, these data open up novel areas of research into a prevention or therapy for this devastating disease.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".