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<b>Immunomodulatory effects of dietary fibre supplementation on lymphocyte populations, cytokine and immunoglobulin A production</b> (39.16)

2009· article· en· W69508677 on OpenAlexaff
Mark Gannon, S. J. D. Brooks, Martin Kalmokoff, Jayadev Raju, L. Brent Selinger, Douglas Inglis, Julia M. Green-Johnson

Bibliographic record

VenueThe Journal of Immunology · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsLethbridge CollegeAgriculture and Agri-Food CanadaHealth CanadaUniversity of LethbridgeOntario Tech University
Fundersnot available
KeywordsImmune systemBranBiologyWeanlingImmunologyMesenteric lymph nodesPopulationLymphocyteEndocrinologyMedicine

Abstract

fetched live from OpenAlex

Abstract Gastrointestinal microflora has been shown to have a bi-directional relationship with the host immune system. A variety of fermentable carbohydrate polymers largely pass through the small intestine, providing fermentable substrates for gut microflora. Dietary fibre supplementation may provide a strategy for manipulating the intestinal bacterial profile, changing the interaction with the mucosal immune system, thereby modulating the host immune system. Over a six week trial, 30 weanling BioBreeding rats were fed either control diet alone or supplemented with oat bran or wheat bran fibre. We have shown that wheat bran fibre increases mesenteric lymph node (MLN) B lymphocyte numbers, and decreases systemic IL4 production, MLN T lymphocytes, and intestinal IgA, concurrent with increased colonic bacterial population diversity. We also observed no evidence of pro-inflammatory responses resulting from dietary fibre supplementation. This lends support to the hypothesis that dietary fibre may modulate the host immune system through modification of the gut microflora profile. The research is funded by the Advanced Foods and Materials Network

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

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)0.0030.000

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 head0.010
GPT teacher head0.263
Teacher spread0.254 · 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 designObservational
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

Citations1
Published2009
Admission routes1
Has abstractyes

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