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<i>Giardia duodenalis</i> : A model of pathogen‐mediated disruptions in the human microbiota in leading to the development of chronic gastrointestinal disease

2012· article· en· W3176939660 on OpenAlexafffund
Jennifer Beatty, Sarah Akierman, Howard Ceri, Kevin P. Rioux, Paul L. Beck, André G. Buret

Bibliographic record

VenueThe FASEB Journal · 2012
Typearticle
Languageen
FieldImmunology and Microbiology
TopicParasitic Infections and Diagnostics
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGiardiaBiofilmMicrobiologyEnterocyteBiologyPathogenBifidobacteriumHuman pathogenIrritable bowel syndromeBacteriaSmall intestineLactobacillusMedicine

Abstract

fetched live from OpenAlex

Giardia duodenalis is a key pathogen causing post‐infectious Irritable Bowel Syndrome (PI‐IBS) symptoms. Underlying mechanisms are unknown, but disruptions in species distribution of the intestinal microbiota in IBS patients have been reported. The intestinal microflora exists in biofilm communities, and the effects of enteropathogens on this phenotype, in the context of PI‐IBS, remain obscure. Aim To study effects of Giardia on the structure, species, and pathogenic profile of microflora biofilms. Methods Representative intestinal mucosal biofilms were cultured from human colonic mucosal biospy samples. Results Giardia enhances the presence of Clostridiales spp. in microflora biofilms. Giardia promotes planktonic growth in microflora biofilms by disrupting normal polysaccharide production. Giardia ‐exposed biofilms induce higher levels of enterocyte apoptosis than ones incubated with control biofilms. Conclusion Giardia exposed biofilms exhibit altered structure and species composition in human microflora biofilms, and promote enterocyte apoptosis, highlighting detrimental effects of a pathogen‐modified microflora in the bowel. Supported by NSERC

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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.027
GPT teacher head0.280
Teacher spread0.253 · 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
Published2012
Admission routes2
Has abstractyes

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