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Normal Breast Milk Limits the Development of Colitis in IL-10–Deficient Mice

2002· article· en· W2005158731 on OpenAlexafffund
Karen Madsen, Richard N. Fedorak, Michele M. Tavernini, Jason Doyle

Bibliographic record

VenueInflammatory Bowel Diseases · 2002
Typearticle
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchFondation pour la Recherche MédicaleCrohn's and Colitis Foundation of CanadaCrohn's and Colitis Foundation
KeywordsBreast milkColitisMedicineInternal medicineGastroenterologyBiologyBiochemistry

Abstract

fetched live from OpenAlex

BACKGROUND AND AIMS: This study examined the role of breast milk in neonatal bacterial colonization of the colon and disease progression in IL-10-deficient mice. METHODS: IL-10-deficient mice were cross-fostered at birth and raised until weaning with a normal mother. Results were compared with normal pups cross-fostered to an IL-10-deficient mother. Mice were examined at various ages for histologic disease, levels of colonic bacteria, and proinflammatory cytokine secretion. RESULTS: IL-10-deficient mice that had been cross-fostered to a normal mother demonstrated normal levels of colonic adherent bacteria and reduced TNFalpha and IFN gamma secretion at 2 to 12 weeks of age. Histologic disease was significantly reduced up to 12 weeks of age. Normal mice cross-fostered to an IL-10-deficient mother had increased levels of adherent bacteria at 2 and 4 weeks and increased IFN gamma secretion. This group also demonstrated slight inflammation up until 12 weeks of age. CONCLUSION: Breast milk has a role in neonatal bacterial colonization. Changing the luminal environment of IL-10-deficient mice during the neonatal period alters the natural disease course.

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 score0.002
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.247
Teacher spread0.229 · 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

Citations55
Published2002
Admission routes2
Has abstractyes

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