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Record W2103243010 · doi:10.1542/neo.10-4-e191

Early Life Stress Induces Both Acute and Chronic Colonic Barrier Dysfunction

2009· article· en· W2103243010 on OpenAlexaff
Mélanie G. Gareau, Eytan Wine, Philip M. Sherman

Bibliographic record

VenueNeoReviews · 2009
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineIrritable bowel syndromeIntestinal permeabilityBarrier functionDiseaseMaternal deprivationChronic stressInflammatory bowel diseaseInternal medicineImmunology

Abstract

fetched live from OpenAlex

Exposure to stress in early life can have a profound impact on health in later life, including intestinal pathology. Maternal separation is a well-established and reproducible model of early life stress in rodents that leads to the development of mood disorders and altered intestinal function, including visceral hypersensitivity, colonic dysmotility, and increased intestinal permeability. In this article, we highlight the consequences of disruption of normal programming after exposure to maternal separation in neonates: the development of intestinal alterations in both neonatal and adult animals as well as the accompanying behavioral changes. Mechanisms of action include corticotropin-releasing factor (CRF) and nerve growth factor (NGF), which signal both in the brain and in the periphery. Exposure to stress in early life also can alter bacterial colonization, which is prevented by treatment with probiotic organisms. We conclude by highlighting the link between stress and colonic permeability in humans, including the increased risk of disease relapse in irritable bowel syndrome (IBS) and inflammatory bowel diseases (IBD).

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.290
Teacher spread0.260 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations13
Published2009
Admission routes1
Has abstractyes

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