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Record W2015209966 · doi:10.1161/atvbaha.107.146068

In Vivo Reverse Cholesterol Transport From Macrophages Lacking ABCA1 Expression Is Impaired

2007· article· en· W2015209966 on OpenAlexaff
Mingdong Wang, Vivian Franklin, Yves L. Marcel

Bibliographic record

VenueArteriosclerosis Thrombosis and Vascular Biology · 2007
Typearticle
Languageen
FieldMedicine
TopicCholesterol and Lipid Metabolism
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsABCA1Reverse cholesterol transportCholesterolATP Binding Cassette Transporter 1In vivoLiver X receptorTangier diseaseEffluxMacrophageEndocrinologyBiologyInternal medicineChemistryTransporterMedicineIn vitroBiochemistryLipoprotein

Abstract

fetched live from OpenAlex

BACKGROUND: ATP-binding cassette transporter A1 (ABCA1) is a key mediator of cholesterol efflux to apoA-I in cholesterol loaded macrophages, a first step of reverse cholesterol transport (RCT) in vivo. Macrophage specific abca1 inactivation or overexpression, respectively, accelerated or suppressed the development of atherosclerosis in mouse models. However, it is yet to be established that the ABCA1 effect is related to specific changes in RCT from the macrophages in vivo. METHODS AND RESULTS: one marrow-derived macrophages from abca1-/- or abca1+/- mice were labeled with 3H-cholesterol-AcLDL or 3H-cholesterol-LDL and injected into abca1+/+ abca1+/- or abca1-/- mice. When injected into abca1+/+ mice, return of 3H-cholesterol from labeled abca1-/- macrophages to serum, liver, bile, and feces was reduced by 50% (P=0.01) compared with control. When labeled wild-type macrophages were injected into abca1-/- mice, as compared with wild-type mice, the return of 3H-cholesterol to serum, liver, bile, and feces was also reduced. CONCLUSIONS: ABCA1 expression in macrophages contributes significantly to in vivo macrophage RCT. The important residual RCT observed from abca1-/- macrophages highlight the functionality of transporters that efflux to HDL.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.611
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.028
GPT teacher head0.297
Teacher spread0.269 · 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 designObservational
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

Citations74
Published2007
Admission routes1
Has abstractyes

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