MétaCan
Menu
Back to cohort
Record W2100455028 · doi:10.1194/jlr.m000596

Arylacetamide deacetylase attenuates fatty-acid-induced triacylglycerol accumulation in rat hepatoma cells

2009· article· en· W2100455028 on OpenAlexafffund
Vivien Lo, Bruce D. Erickson, Michaela Thomason-Hughes, Kerry W.S. Ko, Vernon W. Dolinsky, Randy Nelson, Richard Lehner

Bibliographic record

VenueJournal of Lipid Research · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid metabolism and biosynthesis
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsBiochemistryFatty acidLipid metabolismChemistryBeta oxidationApolipoprotein BIntracellularLipid dropletSecretionEnzymeHormone-sensitive lipaseBiologyEndocrinologyLipaseCholesterol

Abstract

fetched live from OpenAlex

Mobilization of hepatic triacylglycerol stores provides substrates for mitochondrial beta-oxidation and assembly of VLDLs; however, the identity of lipolytic enzymes involved in the regulation of this process remains largely unknown. Arylacetamide deacetylase (AADA) shares homology with hormone-sensitive lipase and therefore could potentially participate in hepatic lipid metabolism, including the regulation of hepatic triacylglycerol levels. We have established McArdle-RH7777 (rat hepatoma) cell lines stably expressing mouse AADA cDNA and performed metabolic labeling as well as lipid mass analyses. Expression of AADA cDNA in McArdle-RH7777 cells significantly reduced intracellular triacylglycerol levels and apolipoprotein B secretion and increased fatty acid oxidation. These results suggest that fatty acids released by AADA-mediated hydrolysis of lipids are channeled for -oxidation rather than for the assembly of lipoproteins.

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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.074
GPT teacher head0.374
Teacher spread0.300 · 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

Citations48
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Lipid ResearchSame topicLipid metabolism and biosynthesisFrench-language works237,207