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Record W2791202675 · doi:10.1093/jcag/gwy009.020

A20 GUT MICROBIOTA-DIET INTERACTION ALTER INTESTINAL MAST CELL NUMBERS AND DISTRIBUTION IN THE HUMANIZED IBS MOUSE MODEL

2018· article· en· W2791202675 on OpenAlexaff
Chiko Shimbori, Giada De Palma, David E. Reed, Marc Pigrau, Jun Lü, Y Zhang, Yang Yu, Nestor N. Jiménez-Vargas, Jessica Sessenwein, Cintya D. Lopez Lopez, Josue O. Jaramillo Polanco, Elena F. Verdú, Stephen M. Collins, Alan Lomax, Michael Beyak, S Vanner, Přemysl Berčík

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2018
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal motility and disorders
Canadian institutionsQueen's UniversityKingston General HospitalMcMaster University
Fundersnot available
KeywordsGut floraBiologyImmune systemIntestinal permeabilityMast cellTryptaseIleumHistamineInternal medicineImmunologyEndocrinologyMedicine

Abstract

fetched live from OpenAlex

Growing evidence suggests that immune activation and gut microbiota are involved in the pathophysiology of IBS. We have recently demonstrated that a diet low in fermentable oligosaccharides, disaccharides, monosaccharides and polyols (FODMAP) improved symptoms in IBS patients and this was associated with lower urinary histamine and changes in the microbiota composition. A high FODMAP diet in germ-free mice colonized with IBS patient microbiome modulated motility, permeability, and visceral sensitivity. However, the underlying mechanisms are unclear. To investigate the interactions of host’s immune system and intestinal microbiota in response to FODMAPs in the humanized IBS mouse model. Germ-free NIH Swiss mice were colonized with fecal microbiota from two IBS patients (non-constipation) with a high (HH) or low (LH) urinary histamine (n=24 mice/patient), and one healthy control (HV) (n=8). SPF mice (n=8) were included as additional controls. Mice were assigned to a custom-made low or high FODMAP diet (LF and HF, respectively). Microbiota composition was analysed by 16S rRNA gene sequencing. At sacrifice, intestinal tissues were collected for immunohistochemistry (c-kit staining) and immunofluorescence (tryptase, PGP9.5, and Substance P) detection of mast cell and nerves. HH colonized mice receiving HF diet had increased number of mast cells (c-kit positive cells) in both small intestine and colon compared to HH mice on a LF diet (Effect of diet x microbiota: p=0.041, F(1,32)=4.51 for small intestine, and p=0.029, F(1,30)=5.25 for colon). No differences were observed in the colon and small intestine of LH colonized mice. Immunofluorescent staining of colonic and small intestinal sections revealed high number of tryptase positive mast cells in HH colonized mice on HF diet. Moreover, the majority of the mast cells were in close proximity of nerve fibers (PGP9.5 positive) (Fig 1). In HH colonized mice, colonic mast cell numbers were negatively correlated with the relative abundance of Adlercreutzia spp, Oscillospira and Ruminococcus spp. Similarly, in the small intestine of HH colonized mice, mast cell numbers negatively correlated with the relative abundance of Blautia, Ruminococcus, and Lactobacillus spp. A high fermentable diet alters intestinal microbiota composition only in mice colonized with microbiota from a patient with high urinary histamine. These changes are associated with increased numbers of mast cells in both the colon and small intestine. Furthermore, mast cells seem to closely interact with neurons, likely contributing to the functional changes observed in these mice. CIHRNIH

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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.011
GPT teacher head0.237
Teacher spread0.225 · 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
Published2018
Admission routes1
Has abstractyes

Explore more

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