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Record W3206010491 · doi:10.3390/ijms222111365

Microbiota-Immune Interactions in Ulcerative Colitis and Colitis Associated Cancer and Emerging Microbiota-Based Therapies

2021· review· en· W3206010491 on OpenAlex

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.

Bibliographic record

VenueMDPI (MDPI AG) · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsMcMaster University
Fundersnot available
KeywordsUlcerative colitisColitisImmune systemGut floraColorectal cancerFecal bacteriotherapyInflammatory bowel diseaseImmunologyMedicineCancerMicrobiomeBiologyBioinformaticsDiseaseMicrobiologyInternal medicineAntibioticsClostridium difficile

Abstract

fetched live from OpenAlex

Ulcerative colitis (UC) is a chronic autoimmune disorder affecting the colonic mucosa. UC is a subtype of inflammatory bowel disease along with Crohn’s disease and presents with varying extraintestinal manifestations. No single etiology for UC has been found, but a combination of genetic and environmental factors is suspected. Research has focused on the role of intestinal dysbiosis in the pathogenesis of UC, including the effects of dysbiosis on the integrity of the colonic mucosal barrier, priming and regulation of the host immune system, chronic inflammation, and progression to tumorigenesis. Characterization of key microbial taxa and their implications in the pathogenesis of UC and colitis-associated cancer (CAC) may present opportunities for modulating intestinal inflammation through microbial-targeted therapies. In this review, we discuss the microbiota-immune crosstalk in UC and CAC, as well as the evolution of microbiota-based therapies.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.957
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.025
GPT teacher head0.340
Teacher spread0.315 · 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