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Record W4391873679 · doi:10.1093/jcag/gwad061.005

A5 DEVELOPMENT OF A PRE-CLINICAL MOUSE MODEL TO INVESTIGATE ADVERSE FOOD REACTIONS IN INTESTINAL INFLAMMATION

2024· article· en· W4391873679 on OpenAlexaff
B Barbosa da Luz, L Rondeau, Rammy Dang, Alberto Caminero

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsMcMaster University
Fundersnot available
KeywordsInflammationAdverse effectMedicineInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background Patients with chronic intestinal conditions, including inflammatory bowel disease (IBD), experience diverse food-related adverse reactions. However,, the precise mechanisms of food intolerances in IBD remains unclear. Emerging evidence suggests that altered diet-microbiota interactions can contribute to the development of IBD. Previously we shown that intestinal microbiota plays an important role in the development of food intolerances. We hypothesize that microbial alterations in IBD patients facilitate adverse reactions to foods. Aims To establish a preclinical mouse model to study adverse food reactions in intestinal inflammation. Methods Eight-week-old C57BL/6 mice were treated with 3% dextran sodium sulfate (DSS) for 5 days, then divided into three groups. The first group was sensitized to dairy protein (3% casein and 3% whey), using 4 oral administrations of cholera toxin over 2 weeks, without any further diet intervention. The second group was also sensitized to casein and whey, then after 1 week of recovery, the mice were subsequently place on a chow containing casein and whey. Finally, the third group was subjected to diet intervention without sensitization. The same experiment was repeated in a different subset of C57BL/6 mice which included a second cycle of DSS (1.5%) during the dietary interventions. Markers of intestinal inflammation (disease activity index (DAI), histological damage, cell infiltration and pro-inflammatory genes expression (NanoString)) and intestinal microbiota were analysed after 1 week of the diet intervention. Results Mice previously sensitized on the dairy diet exhibited an enhanced activation of immune cells after intestinal inflammation. While the histological damage score did not reveal significant differences among experimental groups, the sensitized group under dairy intervention exhibited an elevated level of immune cell infiltration, increasing the polymorphonuclear, CD3+ and mast cells. Gene expression also revealed that dairy induced the expression of inflammatory genes, such as C6, Arg1, Tnf, Il6, Cxcl9 and Cxcl10. When animals are subjected to a second DSS-cycle, dairy worsen colitis in mice previously sensitized, as shown by higher DAI compared to group with control diet and dairy diet without sensitization. Conclusions In the context of intestinal inflammation, dairy protein leads to immune activation characterized by an increase in polymorphonuclear cells, mast cells and lymphocytes, as well as worsening colitis. Future studies using this model will provide valuable insights into the role of intestinal microbiota in food intolerances associated with intestinal inflammation. Funding Agencies CCC

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)0.001
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.002

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 head0.264
Teacher spread0.247 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

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