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Record W2482579890 · doi:10.2337/db16-0114

Impaired Cardiolipin Biosynthesis Prevents Hepatic Steatosis and Diet-Induced Obesity

2016· article· en· W2482579890 on OpenAlexafffund
Laura Cole, Edgard M. Mejia, Marilyne Vandel, Genevieve C. Sparagna, Steven M. Claypool, Laura Dyck-Chan, Julianne Klein, Grant M. Hatch

Bibliographic record

VenueDiabetes · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsShared HealthUniversity of ManitobaChildren's Hospital Research Institute of Manitoba
FundersNational Heart, Lung, and Blood InstituteNational Institutes of HealthResearch ManitobaBarth Syndrome Foundation
KeywordsCardiolipinInsulin resistanceEndocrinologySteatosisInternal medicineInner mitochondrial membraneMitochondrionBiologyFatty liverSteatohepatitisBeta oxidationType 2 diabetesInsulinDiabetes mellitusMetabolismPhospholipidMedicineBiochemistryMembrane

Abstract

fetched live from OpenAlex

Mitochondria are the nexus of energy metabolism, and consequently their dysfunction has been implicated in the development of metabolic complications and progression to insulin resistance and type 2 diabetes. The unique tetra-acyl phospholipid cardiolipin (CL) is located in the inner mitochondrial membrane, where it maintains mitochondrial integrity. Here we show that knockdown of Tafazzin (TAZ kd), a CL transacylase, in mice results in protection against the development of obesity, insulin resistance, and hepatic steatosis. We determined that hypermetabolism protected TAZ kd mice from weight gain. Unexpectedly, the large reduction of CL in the heart and skeletal muscle of TAZ kd mice was not mirrored in the liver. As a result, TAZ kd mice exhibited normal hepatic mitochondrial supercomplex formation and elevated hepatic fatty acid oxidation. Collectively, these studies identify a key role for hepatic CL remodeling in regulating susceptibility to insulin resistance and as a novel therapeutic target for diet-induced 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 score0.106
Threshold uncertainty score0.365

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 head0.011
GPT teacher head0.219
Teacher spread0.208 · 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

Citations61
Published2016
Admission routes2
Has abstractyes

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