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Record W2921790038 · doi:10.1093/jcag/gwz006.045

A46 FECAL β-DEFENSIN LEVELS AS A RELIABLE BIOMARKER OF INTESTINAL DYSBIOSIS

2019· article· en· W2921790038 on OpenAlexaff
Z Saqib, Giada De Palma, Jun Lü, Přemysl Berčík, Stephen M. Collins

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDysbiosisGut floraImmunologyFecesImmune systemBiomarkerIrritable bowel syndromeProinflammatory cytokineInflammationAntibioticsMicrobiomeBiologyPathogenesisMicrobiologyMedicineInternal medicineBioinformatics

Abstract

fetched live from OpenAlex

Dysbiosis is defined as alterations or instability in gut microbial composition resulting in altered host function. It is triggered by many environmental factors and has been implicated in the pathogenesis of the Irritable Bowel Syndrome (IBS). Recent focus on the putative role of intestinal microbiome generating low grade inflammation and immune activation in IBS has increased the need for a marker of dysbiosis. β-defensins (β-def) are inducible antimicrobial peptides secreted by diverse cell types in response to pathogen encounter or pro-inflammatory cytokines. Studies in IBS patients show that dysbiosis results in skewing of innate mucosal immunity toward a proinflammatory response (increased β-def levels) in the absence of macroscopic signs of inflammation. Our lab recently demonstrated that colonizing germ-free mice with IBS microbiota results in IBS-like changes in gut function and increase in colonic β-def expression in recipient mice. To investigate whether fecal β-def levels constitute a reliable biomarker of dysbiosis. We induced dysbiosis using different protocols including single antibiotic (Neomycin), an antibiotic cocktail (ABC) or a high-fat/high-sugar diet (HF/HSD). Mice (n=20) were divided into 3 groups and all received 1 week of treatment, preceded and followed by 1-week long baseline and recovery periods. The single antibiotic was administered to C57/BL6 ASF mice, the ABC was given to C57/BL6 SPF mice and another group of C57/BL6 SPF mice received HF/HSD. Stool samples were collected every day for 16S rRNA gene profiling, qPCR analysis of total bacterial load and fecal β-def levels analysis by an ELISA. SPF mice receiving the ABC showed a significant decrease in β-def levels (p<0.0001). Similar differences in β-def levels were observed in ABC treated females. Changes in microbial composition (Bacteroidetes, Firmicutes, Proteobacteria, Tenericutes, TM7) in ABC treated mice significantly correlated with β-def levels. In ASF mice, neomycin administration led to significant changes in β-def levels and alpha- diversity. Unlike ASF males, females showed a significant correlation between changes in microbial composition (Bacteroidetes and Verrucomicrobia) and β-def levels. The HF/HSD transiently altered the microbial richness (baseline vs. treatment: p=0.042; treatment vs. recovery: p=0.045) and diversity (baseline vs. treatment: p=0.009; treatment vs. recovery: p=0.021) but no significant correlations were found between β-def levels and microbial composition. There were significant differences between β-def levels in ASF and SPF treated mice. Our results suggest that innate immune activation is differentially affected in ASF and SPF mice depending on the microbial complexity of the microbiota. These findings indicate that fecal β-defensins are a putative biomarker for dysbiosis and warrant further investigation. CIHR

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.009
GPT teacher head0.234
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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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