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Record W2886962234 · doi:10.1530/joe-18-0173

Adipocyte HDAC4 activation leads to beige adipocyte expansion and reduced adiposity

2018· article· en· W2886962234 on OpenAlexfundno aff
Esther Paulo, Dongmei Wu, Peter Hecker, Yun Zhang, Biao Wang

Bibliographic record

VenueJournal of Endocrinology · 2018
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsnot available
FundersUniversity of California, San FranciscoNational Institutes of HealthMcGill UniversityNational Institute of Diabetes and Digestive and Kidney DiseasesLarry L. Hillblom Foundation
KeywordsAdipocyteInternal medicineEndocrinologyHDAC4White adipose tissueAdipose tissueBiologyMedicineHistone deacetylaseBiochemistryHistone

Abstract

fetched live from OpenAlex

Numerous studies have suggested that beige adipocyte abundance is correlated with improved metabolic performance, but direct evidence showing that beige adipocyte expansion protects animals from the development of obesity is missing. Previously, we have described that the liver kinase b1 (LKB1) regulates beige adipocyte renaissance in subcutaneous inguinal white adipose tissue (iWAT) through a class IIa histone deacetylase 4 (HDAC4)-dependent mechanism. This study investigates the physiological impact of persistent beige adipocyte renaissance in energy homeostasis in mice. Here we present that the transgenic mice H4-TG, overexpressing constitutively active HDAC4 in adipocytes, showed beige adipocyte expansion in iWAT at room temperature. H4-TG mice exhibited increased energy expenditure due to beige adipocyte expansion. They also exhibited reduced adiposity under both normal chow and high-fat diet (HFD) feeding conditions. Specific ablation of beige adipocytes reversed the protection against HFD-induced obesity in H4-TG mice. Taken together, our results directly demonstrate that beige adipocyte expansion regulates adiposity in mice and targeting beige adipocyte renaissance may present a novel strategy to tackle obesity in 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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.258
Threshold uncertainty score0.585

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.026
GPT teacher head0.314
Teacher spread0.288 · 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

Citations17
Published2018
Admission routes1
Has abstractyes

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