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Cholesteryl Ester Transfer Protein (CETP) Expression Protects Against Diet Induced Atherosclerosis in SR-BI Deficient Mice

2007· article· en· W2108345908 on OpenAlexaff
Christopher Harder, Paulina Lau, Andrew Meng, Stewart C. Whitman, Ruth McPherson

Bibliographic record

VenueArteriosclerosis Thrombosis and Vascular Biology · 2007
Typearticle
Languageen
FieldMedicine
TopicCholesterol and Lipid Metabolism
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCholesterylester transfer proteinTransgeneEndocrinologyInternal medicineGenetically modified mouseCholesterolHigh-density lipoproteinLipoproteinBiologyApolipoprotein BRatónChemistryMedicineGeneBiochemistry

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine whether expression of the human CETP transgene protects against diet-induced atherosclerosis in SR-BI deficient mice. METHODS AND RESULTS: SR-BI deficient (-/-) mice were crossed with CETP transgenic (CETPtg) mice to produce a colony of SR-BI(-/-) x CETPtg mice in a C57Bl/6 background. Age and sex matched groups of genetically modified and wild-type C57Bl/6 mice were fed a high fat, high cholesterol diet for 22 weeks. In both wild-type and SR-BI(-/-) mice, expression of the CETP transgene reduced the cholesterol content and increased the density of lipoprotein particles in the HDL density range. In SR-BI(-/-) x CETPtg mice, CETP activity inversely correlated with total plasma cholesterol levels and shifted the buoyant HDL typical of SR-BI deficiency toward a more normal density HDL particle. Atherosclerosis at the level of the aortic arch was evident in both male and female SR-BI deficient mice but occurred to a greater extent in the females. Expression of CETP markedly attenuated the development of atherosclerosis in SR-BI deficient mice fed an atherogenic diet (P<0.003). CONCLUSIONS: Expression of the human CETP transgene protects SR-BI deficient mice from atherosclerosis, consistent with a role for CETP in remodeling HDL and providing an alternative pathway for the selective uptake of HDL-CE by the liver.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.829
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.040
GPT teacher head0.284
Teacher spread0.244 · 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.

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
Published2007
Admission routes1
Has abstractyes

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