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Record W3010646857 · doi:10.1186/s12866-020-01724-8

The influence of blood on the human gut microbiome

2020· article· en· W3010646857 on OpenAlex
Thierry Chénard, Mandy Malick, Jean Y. Dubé, Éric Massé

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBMC Microbiology · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsUniversité de Sherbrooke
FundersCanadian Institutes of Health ResearchMerck Sharp and Dohme
KeywordsPrevotellaFaecalibacterium prausnitziiMicrobiomeBiologyRoseburiaBacteroidesFecesPhysiologyGut floraHuman microbiomeColorectal cancerImmunologyCancerInternal medicineMicrobiologyMedicineBioinformaticsBacteriaGenetics

Abstract

fetched live from OpenAlex

BACKGROUND: Colorectal cancer (CRC) is one of the prevailing causes of cancer mortality in the world. A common screening test for CRC is based on the human hemoglobin immunochemical based fecal occult blood test (iFOBT), which consists in the detection of blood in the patient's stool. In addition to iFOBT, recent studies support the use of the gut microbiome as a biomarker for CRC prediction. However, these studies did not take into account the effect of blood itself on the microbiome composition, independently of CRC. Therefore, we investigated the microbiome of patients undergoing the iFOBT screening in order to determine the effect of blood alone. Our cohort consisted of patients who had no blood in their stools (n = 265) or did have blood but no underlying precancerous or cancerous lesions (n = 235). We also identified bacterial taxa specifically associated with the presence of blood in stools. RESULTS: We observed significant differences in the intestinal bacterial composition that could be solely caused by the presence of blood in stools. More precisely, we identified 12 bacterial species showing significant differences in abundance between both our study groups. These species, Bacteroides uniformis, Collinsella aerofaciens, Eggerthella lenta and Clostridium symbiosum demonstrated increased abundance in the presence of blood. In contrast, the species Prevotella copri, Coprococcus eutactus and catus, Faecalibacterium prausnitzii, Roseburia faecis, Blautia obeum, Gemmiger formicilis and Clostridium celatum showed decreased abundance in patients with blood in their stools. Notably, we found multiple taxa that were reported in previous studies linking microbiome composition and diseases. CONCLUSIONS: We show that, in the absence of disease, blood in the stools has a major influence on the composition of the microbiome. Our data suggest that blood itself should be taken into consideration when investigating the microbiome signatures of intestinal diseases.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.158
Threshold uncertainty score0.407

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.254
Teacher spread0.237 · 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