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Record W2791747253 · doi:10.1093/jcag/gwy008.300

A299 IDENTIFICATION OF PATHOGENIC BACTERIAL STRAINS IN PAEDIATRIC PATIENTS WITH INFLAMMATORY BOWEL DISEASES USING IMMUNOGLOBULIN G AS A MARKER OF VIRULENCE

2018· article· en· W2791747253 on OpenAlexaff
Misagh Alipour, Heather Armstrong, Rosica Valcheva, Deenaz Zaidi, Juan Jovel, Yuefei Lou, Andrew L. Mason, Gane Ka‐Shu Wong, Karen Madsen, Levinus A. Dieleman, Matthew Carroll, Hien Q. Huynh, Eytan Wine

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2018
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBacterial Infections and Vaccines
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsAntibodyMicrobiologyInflammatory bowel diseaseBiologyPathogenic bacteriaUlcerative colitisFirmicutesImmune systemImmunoglobulin GImmunologyBacteriaMedicine16S ribosomal RNADiseasePathologyGenetics

Abstract

fetched live from OpenAlex

Inflammatory bowel diseases (IBD), including Crohn disease (CD) and ulcerative colitis (UC), are a group of chronic and severely debilitating gastrointestinal disorders, with an exacerbated immune response to the gut microbiota. We hypothesized that pathogenic bacteria are more likely to be bound by immunoglobulin (Ig) G antibodies and identification of these strains could help identify mechanisms of immune activation. Aspirate washes were obtained from the terminal ileum of pediatric IBD and non-IBD patients during endoscopy. Samples were fixed in paraformaldehyde and stringently washed to separate bacteria. Prior to fluorescence-activated cell sorting (FACS), samples were stained with propidium iodide (PI) and an anti-IgG fluorescent antibody with proper controls to differentiate bacteria bound by IgG (IgG+) from all others (IgG-). Validation in a select set of samples involved image cytometry. DNA was extracted from sorted bacteria using bead beating extraction and phenol/chloroform purification. Analysis of bacterial DNA samples was completed using the Ilumina MiSeq platform for 16S rRNA gene sequencing. Quality of patient bacterial DNA samples was used to identify those suitable to be sequenced resulting in 36 total washes from children without IBD (n=10), and with CD (n=17) or UC (n=9). Firmicutes and Bacteroidetes phyla were most commonly identified; however, no significant differences were found between IBD and non-IBD controls upon examining the composition of the ileal mucosa-associated microbiome. There was a 2 and 1.5 fold increase in the overall ratio of IgG+/IgG- bacteria in CD and UC, respectively. In CD, there was an increase in IgG+/IgG- ratio of both Bacteroidetes and Proteobacteria phyla. In UC this ratio was increased for Actinobacteria. IgG binding favored specific family level strains including Porphyromonadaceae (Bacteroidetes) and Enterobacteriaceae (Proteobacteria) in CD; Barnesiellaceae (Bacteroidetes) and Bifidobacteriaceae (Actinobacteria) in UC; and Clostridiaceae and Veillonellaceae (Firmicutes) in non-IBD, although considerable variation was noted between patients. This study demonstrated selective increase of mucosa associated bacteria bound by IgG in the ileum of pediatric IBD patients compared to non-IBD. Further use of this method in larger cohort studies can identify individual microbes as therapeutic targets facilitating the development of targeted diagnostic and improved therapeutic approaches for IBD. CCCCCFC, AIHS

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.004
GPT teacher head0.201
Teacher spread0.196 · 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
Published2018
Admission routes1
Has abstractyes

Explore more

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