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Record W3042703480 · doi:10.1159/000510212

The Role of Gut Microbiome in Autoimmune Uveitis

2020· review· en· W3042703480 on OpenAlexaff
Xiangyu Fu, Yongjiang Chen, Danian Chen

Bibliographic record

VenueOphthalmic Research · 2020
Typereview
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsDysbiosisMicrobiomeImmunologyMolecular mimicryFecal bacteriotherapyImmune systemUveitisAutoimmunityBiologyGut floraPathogenesisAutoimmune diseaseMedicineAntibioticsBioinformaticsMicrobiologyAntibody

Abstract

fetched live from OpenAlex

The gut microbiome has important physiological functions and plays an indispensable role in the human body. Currently, there are an increasing number of studies revealing the close correlation between dysbiosis of the gut microbiome and a variety of autoimmune diseases, including autoimmune uveitis. This brief review summarizes recent literature regarding the relationship between dysbiosis and the occurrence and development of autoimmune uveitis. Dysbiosis participates in the pathogenesis of autoimmune uveitis largely by 4 mechanisms: antigenic mimicry, disturbance of intestinal immune homeostasis, destruction of the intestinal barrier, and reduction of beneficial anti-inflammatory metabolites. Further elucidation of these mechanisms will facilitate the treatment of the gut-microbiome-relevant autoimmune diseases by potential therapeutic strategies, such as antibiotics, probiotics, diet modifications, and fecal microbial transplantation.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.116
GPT teacher head0.460
Teacher spread0.344 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations44
Published2020
Admission routes1
Has abstractyes

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