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Record W2750464235 · doi:10.1002/eji.201646739

Adipose‐tissue regulatory T cells: Critical players in adipose‐immune crosstalk

2017· review· en· W2750464235 on OpenAlexafffund
Maike Becker, Megan K. Levings, Carolin Daniel

Bibliographic record

VenueEuropean Journal of Immunology · 2017
Typereview
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsBC Children's HospitalUniversity of British Columbia
FundersHelmholtz Zentrum MünchenDeutsche ForschungsgemeinschaftBC Children's HospitalCanadian Diabetes Association
KeywordsAdipose tissueFOXP3CrosstalkBiologyInflammationImmune systemImmunologyType 2 diabetesCell biologyDiabetes mellitusEndocrinology

Abstract

fetched live from OpenAlex

Abstract Obesity and type‐2 diabetes (T2D) are associated with metabolic defects and inflammatory processes in fat depots. FoxP3 + regulatory T cells (Tregs) control immune tolerance, and have an important role in controlling tissue‐specific inflammation. In this mini‐review we will discuss current insights into how cross‐talk between T cells and adipose tissue shapes the inflammatory environment in obesity‐associated metabolic diseases, focusing on the role of CD4 + T cells and Tregs. We will also highlight potential opportunities for how the immunoregulatory properties of Tregs could be harnessed to control inflammation in obesity and T2D and emphasize the critical need for more research on humans to establish mechanisms that are conserved in both mice and humans.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.047
GPT teacher head0.344
Teacher spread0.297 · 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.

Study designOther design
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

Citations58
Published2017
Admission routes2
Has abstractyes

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