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Record W2898787162 · doi:10.1139/cjpp-2018-0370

Neonatal intestinal injury induced by maternal separation: pathogenesis and pharmacological targets

2018· review· en· W2898787162 on OpenAlexafffundvenue
Bo Li, Fang Zhou Yu, Adam Minich, Alison Hock, Carol Lee, Agostino Pierro

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2018
Typereview
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsHospital for Sick Children
FundersCanadian Institutes of Health ResearchHospital for Sick Children
KeywordsPathogenesisNecrotizing enterocolitisOxidative stressInflammationBiologyPathologicalIntestinal mucosaEndoplasmic reticulumImmunologyPathologyNeuroscienceMedicineCell biologyEndocrinologyInternal medicine

Abstract

fetched live from OpenAlex

Maternal separation (MS) is a well-studied phenomenon thought to play a role in the pathogenesis of many diseases ranging from neuropsychiatric to early intestinal disorders such as necrotizing enterocolitis. The existing evidence suggests that MS initiates a variety of processes that in turn lead to early intestinal injury. Although there are many theories as to how MS alters normal physiological processes, the exact mechanism of action remains to be elucidated. This review aims to describe some of the pathological processes affecting the intestine that are caused by MS, including (i) brain-gut axis, (ii) intestinal epithelial barrier function, (iii) microbiome, (iv) oxidative stress and endoplasmic reticulum stress, and (v) gut inflammation.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.043
GPT teacher head0.380
Teacher spread0.337 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2018
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Physiology and Pharmacology→Same topicMaternal Mental Health During Pregnancy and Postpartum→French-language works237,207→