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Record W2120674013 · doi:10.2337/db13-0500

Skeletal Muscle Triacylglycerol Hydrolysis Does Not Influence Metabolic Complications of Obesity

2013· article· en· W2120674013 on OpenAlexaff
Mitch T. Sitnick, Mahesh Kumar Basantani, Lingzhi Cai, Gabriele Schoiswohl, Cynthia F. Yazbeck, Giovanna Distéfano, Vladimir B. Ritov, James P. DeLany, Renate Schreiber, Donna B. Stolz, Noah P. Gardner, Petra C. Kienesberger, Thomas Pulinilkunnil, Rudolf Zechner, Bret H. Goodpaster, Paul M. Coen, Erin E. Kershaw

Bibliographic record

VenueDiabetes · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid metabolism and biosynthesis
Canadian institutionsDalhousie University
FundersNational Center for Research ResourcesNational Institute of Diabetes and Digestive and Kidney DiseasesNIH Office of the DirectorNational Cancer InstituteHollings Cancer Center, Medical University of South CarolinaNational Institutes of HealthEndocrine Fellows FoundationUniversity of PittsburghAmerican Diabetes AssociationUniversity of South CarolinaJoslin Diabetes CenterHoward Hughes Medical Institute
KeywordsSkeletal muscleInternal medicineObesityEndocrinologyHydrolysisMedicineChemistryBiochemistry

Abstract

fetched live from OpenAlex

Intramyocellular triacylglycerol (IMTG) accumulation is highly associated with insulin resistance and metabolic complications of obesity (lipotoxicity), whereas comparable IMTG accumulation in endurance-trained athletes is associated with insulin sensitivity (the athlete's paradox). Despite these findings, it remains unclear whether changes in IMTG accumulation and metabolism per se influence muscle-specific and systemic metabolic homeostasis and insulin responsiveness. By mediating the rate-limiting step in triacylglycerol hydrolysis, adipose triglyceride lipase (ATGL) has been proposed to influence the storage/production of deleterious as well as essential lipid metabolites. However, the physiological relevance of ATGL-mediated triacylglycerol hydrolysis in skeletal muscle remains unknown. To determine the contribution of IMTG hydrolysis to tissue-specific and systemic metabolic phenotypes in the context of obesity, we generated mice with targeted deletion or transgenic overexpression of ATGL exclusively in skeletal muscle. Despite dramatic changes in IMTG content on both chow and high-fat diets, modulation of ATGL-mediated IMTG hydrolysis did not significantly influence systemic energy, lipid, or glucose homeostasis, nor did it influence insulin responsiveness or mitochondrial function. These data argue against a role for altered IMTG accumulation and lipolysis in muscle insulin resistance and metabolic complications of obesity.

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 score0.301
Threshold uncertainty score0.426

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 head0.213
Teacher spread0.207 · 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

Citations77
Published2013
Admission routes1
Has abstractyes

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