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Record W2552235278 · doi:10.15252/emmm.201606531

Gut microbiota influences pathological angiogenesis in obesity‐driven choroidal neovascularization

2016· article· en· W2552235278 on OpenAlexafffund
Elisabeth M. M. A. Andriessen, Ariel M. Wilson, Gaëlle Mawambo, Agnieszka Dejda, Khalil Miloudi, Florian Sennlaub, Przemysław Sapieha

Bibliographic record

VenueEMBO Molecular Medicine · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsMcGill UniversityPolytechnique MontréalUniversité de MontréalHôpital Maisonneuve-Rosemont
FundersFoundation Fighting BlindnessNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchAlcon Research InstituteFondation de l'Avenir pour la Recherche Médicale AppliquéeCanadian Diabetes Association
KeywordsChoroidal neovascularizationMacular degenerationGut floraAngiogenesisPathologicalDysbiosisNeovascularizationIntestinal permeabilityMicrobiomeMedicineInflammationImmunologyBiologyPhysiologyPathologyInternal medicineBioinformaticsOphthalmology

Abstract

fetched live from OpenAlex

Age-related macular degeneration in its neovascular form (NV AMD) is the leading cause of vision loss among adults above the age of 60. Epidemiological data suggest that in men, overall abdominal obesity is the second most important environmental risk factor after smoking for progression to late-stage NV AMD To date, the mechanisms that underscore this observation remain ill-defined. Given the impact of high-fat diets on gut microbiota, we investigated whether commensal microbes influence the evolution of AMD Using mouse models of NV AMD, microbiotal transplants, and other paradigms that modify the gut microbiome, we uncoupled weight gain from confounding factors and demonstrate that high-fat diets exacerbate choroidal neovascularization (CNV) by altering gut microbiota. Gut dysbiosis leads to heightened intestinal permeability and chronic low-grade inflammation characteristic of inflammaging with elevated production of IL-6, IL-1β, TNF-α, and VEGF-A that ultimately aggravate pathological angiogenesis.

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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.735
Threshold uncertainty score0.639

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 science0.0000.000
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 head0.009
GPT teacher head0.255
Teacher spread0.247 · 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 teacher head, 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

Citations196
Published2016
Admission routes2
Has abstractyes

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