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Record W1979571494 · doi:10.1002/hep.23813

Tamoxifen Induces Triacylglycerol Accumulation in the Mouse Liver by Activation of Fatty Acid Synthesis

2010· article· en· W1979571494 on OpenAlexafffund
Laura Cole, René L. Jacobs, Dennis E. Vance

Bibliographic record

VenueHepatology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsTamoxifenFatty acid synthesisInternal medicineChemistryEndocrinologyFatty acidFatty liverBiochemistryBiologyMedicineCancerBreast cancer

Abstract

fetched live from OpenAlex

UNLABELLED: Tamoxifen is an anti-estrogen drug widely used for the treatment of hormone-sensitive breast cancer. Approximately 43% of breast cancer patients treated with tamoxifen develop hepatic steatosis. The mechanism or mechanisms by which tamoxifen may induce lipid accumulation in the liver are unclear. Mice were injected with tamoxifen or vehicle (sesame oil containing 1% benzyl alcohol) for 5 consecutive days. In comparison with the vehicle, tamoxifen increased hepatic triacylglycerol levels by 72%. The levels of plasma triacylglycerol were similar between the tamoxifen-treated and control groups. We found increased radiolabeling of triacylglycerol and phospholipids from [(3)H]acetate (∼50%) but not [(14)C]oleate in hepatocytes from tamoxifen-treated mice versus control mice. Fatty acid uptake, triacylglycerol secretion, and fatty acid oxidation remained unchanged in isolated hepatocytes after tamoxifen treatment. The apparent increase in fatty acid synthesis was explained by a marked decrease in the phosphorylation of acetyl coenzyme A carboxylase, which resulted in its activation. CONCLUSION: Our data suggest that increased de novo fatty acid synthesis is the primary event leading to tamoxifen-induced steatosis in the mouse liver. Inhibition of fatty acid synthesis might, therefore, ameliorate steatosis/steatohepatitis in breast cancer patients treated with tamoxifen.

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 score0.100
Threshold uncertainty score0.322

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 head0.022
GPT teacher head0.275
Teacher spread0.253 · 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

Citations107
Published2010
Admission routes2
Has abstractyes

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