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Record W2027656632 · doi:10.1194/jlr.m013177

Plasma-based approach to measure target engagement for liver-targeting stearoyl-CoA desaturase 1 inhibitors

2011· article· en· W2027656632 on OpenAlexaff
France Landry, Chi‐Chung Chan, Zheng Huang, Grégoire Leclair, Chun Sing Li, Renata M. Oballa, Lei Zhang, Kevin P. Bateman

Bibliographic record

VenueJournal of Lipid Research · 2011
Typearticle
Languageen
FieldMedicine
TopicCholesterol and Lipid Metabolism
Canadian institutionsMerck Canada Inc. (Canada)
Fundersnot available
KeywordsMeasure (data warehouse)Stearoyl-CoA DesaturaseChemistryComputational biologyBiochemistryPharmacologyMedicineBiologyComputer scienceGeneData miningGene expression

Abstract

fetched live from OpenAlex

A positive correlation between stearoyl-CoA desaturase (SCD)1 expression and metabolic diseases has been reported in rodents and humans. These findings indicate that SCD1 is a promising therapeutic target for the chronic treatment of diabetes and dyslipidemia. The SCD1 enzyme is expressed at high levels in several human tissues and is required for the biosynthesis of monounsaturated fatty acids, which are involved in many biological processes. Liver-targeted SCD inhibitors were designed to pharmacologically manipulate SCD1 activity in the liver to avoid adverse events due to systemic inhibition. This article describes the development of a plasma-based SCD assay to assess the level of SCD inhibition, which is defined in this article as target engagement. Essentially, animals are dosed with an exogenous deuterated tracer (d7-stearic acid) as substrate, and the converted d7-oleic acid product is measured to monitor SCD1 inhibition. This study reveals that this plasma-based assay correlates with liver SCD1 inhibition and can thus have clinical utility.

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)0.010
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.198
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.212
GPT teacher head0.358
Teacher spread0.146 · 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 designNot applicable
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

Citations13
Published2011
Admission routes1
Has abstractyes

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