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Record W2293839207 · doi:10.1080/19490976.2015.1127481

Different Th17 immunity in gut, liver, and adipose tissues during obesity: the role of diet, genetics, and microbes

2016· article· en· W2293839207 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueGut Microbes · 2016
Typearticle
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsPopulation Health Research InstituteMcMaster University
FundersCanadian Institutes of Health Research
KeywordsBiologyImmune systemImmunityInsulin resistanceGut floraAdipose tissueInflammationObesityDysbiosisImmunologyEndocrinologyInternal medicineMedicine

Abstract

fetched live from OpenAlex

Microbes modify immunometabolism responses linking obesity and type 2 diabetes. Immunity helps maintain a host-microbe symbiosis, but inflammation can promote insulin resistance in tissues that control blood glucose. We were interested in compartmentalization of immune responses during obesity and show here that feeding mice an obesity-causing high-fat diet (HFD) decreased a marker of neutrophil activation and cytokines related to Th17 responses in the gut. A HFD decreased IL-17 and IL-21/22 in the ileum and colon, respectively. A HFD increased IL-17, IL-21/22 and other related Th17 responses in the liver. At the whole tissue level, there is divergence in gut and metabolic tissue Th17 cytokines during diet-induced obesity. Deletion of the bacterial peptidoglycan sensor NOD2 had relatively minor effects on these immune responses. We propose a model where diet-induced obesity promotes a permissive gut immune environment and sets the stage for host genetics to contribute to dysbiosis-driven metabolic tissue inflammation.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score0.344

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 head0.006
GPT teacher head0.219
Teacher spread0.213 · 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