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Record W2969829205 · doi:10.1055/s-0039-1693994

Necrotizing Enterocolitis: State of the Art in Translating Experimental Research to the Bedside

2019· review· en· W2969829205 on OpenAlexaff
Niloofar Ganji, Bo Li, Carol Lee, Rachel Filler, Agostino Pierro

Bibliographic record

VenueEuropean Journal of Pediatric Surgery · 2019
Typereview
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsHospital for Sick ChildrenSickKids Foundation
Fundersnot available
KeywordsNecrotizing enterocolitisMedicineNeonatologyDiseasePathogenesisIntensive care medicineIntestinal mucosaEnterocolitisBioinformaticsPathologyInternal medicinePregnancy

Abstract

fetched live from OpenAlex

Necrotizing enterocolitis (NEC) is a devastating intestinal disease that continues to have high morbidity and mortality among preterm neonates, despite medical advancements in neonatology and neonatal care. To investigate the pathogenesis of the disease and explore novel form of treatment, a variety of experimental models of NEC have been developed and used by various investigators. These experimental models range from in vitro evaluation of intestinal epithelial cells and intestinal organoids to in vivo models of the disease in neonatal mice, rats, and piglets. Most recently, human-derived intestinal organoids have also been developed and investigated. In this review, we will briefly discuss these experimental models and the contributions that they have made to our understanding of NEC. We will also point to the ischemia/reperfusion (I/R) model of intestinal injury which has been used as an indirect model of NEC by some investigators. Advancements in laboratory research into this devastating disease have continued to expand our knowledge on the pathogenesis and prevention of NEC as well as the effectiveness of therapeutic options for management of this severe disease.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.845
Threshold uncertainty score0.717

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.211
GPT teacher head0.416
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations10
Published2019
Admission routes1
Has abstractyes

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