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Record W2790798185 · doi:10.1111/acel.12721

Ablation of <scp>PPAR</scp>γ in subcutaneous fat exacerbates age‐associated obesity and metabolic decline

2018· article· en· W2790798185 on OpenAlexfundno aff
Lingyan Xu, Xinran Ma, Narendra Verma, Dongmei Wang, Oksana Gavrilova, Richard L. Proia, Toren Finkel, Elisabetta Mueller

Bibliographic record

VenueAging Cell · 2018
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood InstituteNational Institutes of HealthChina Postdoctoral Science FoundationNational Natural Science Foundation of ChinaYork UniversityNew York University
KeywordsEndocrinologyInternal medicineBiologyThermogenesisAdipose tissueInsulin resistanceDownregulation and upregulationObesityPeroxisome proliferator-activated receptorThermogeninReceptorGeneMedicine

Abstract

fetched live from OpenAlex

It is well established that aging is associated with metabolic dysfunction such as increased adiposity and impaired energy dissipation; however, the transcriptional mechanisms regulating energy balance during late life stages have not yet been fully elucidated. Here, we show that ablation of the nuclear receptor PPARγ specifically in inguinal fat tissue in aging mice is associated with increased fat tissue expansion and insulin resistance. These metabolic effects are accompanied by decreased thermogenesis, reduced levels of brown fat genes, and browning of subcutaneous adipose tissue. Comparative studies of the effects of PPARγ downregulation in young and mid-aged mice demonstrate a preferential regulation of brown fat gene programs in inguinal fat in an age-dependent manner. In conclusion, our study uncovers an essential role for PPARγ in maintaining energy expenditure during the aging process and suggests the possibility of targeting PPARγ to counteract age-associated metabolic dysfunction.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.260
Teacher spread0.246 · 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 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

Citations46
Published2018
Admission routes1
Has abstractyes

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