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Record W2088464509 · doi:10.1194/jlr.m500133-jlr200

Alternate transcripts expressed in response to diet reflect tissue-specific regulation of ABCA1

2005· article· en· W2088464509 on OpenAlexaff
Roshni R. Singaraja, E. James, Jennifer L. Crim, Henk Visscher, Alu Chatterjee, Michael R. Hayden

Bibliographic record

VenueJournal of Lipid Research · 2005
Typearticle
Languageen
FieldMedicine
TopicCholesterol and Lipid Metabolism
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsABCA1BiologyExonDownregulation and upregulationMessenger RNARNAGene expressionTransgeneGeneMolecular biologyCell biologyGeneticsTransporter

Abstract

fetched live from OpenAlex

ABCA1 is essential for the transport of lipids across plasma membranes and for the maintenance of plasma HDL-cholesterol levels. The transcriptional regulation of ABCA1 is complex and is currently poorly understood. We previously generated human ABCA1 bacterial artificial chromosome transgenic mice that expressed RNA and protein, which allowed us to identify three alternate ABCA1 transcripts. Each transcript arises from different exon 1 sequences (exon1b, exon1c, and exon1d) that are spliced directly into exon 2, which contains the ATG site, and all generate full-length protein. We have now determined the tissue-specific expression of each of these transcripts in humans and mice and have shown that their patterns of expression are similar. Exon1d transcript is predominantly expressed in liver and macrophages and is preferentially increased in the liver in response to a high-fat diet. The exon1b transcript is expressed predominantly in liver, testis, and macrophages, but it is only upregulated in macrophages in response to a high-fat diet. The exon1c transcript is ubiquitously expressed and is upregulated in the brain, stomach, and other tissues in mice on a high-fat diet. Our data indicate that specific transcripts in different tissues play key roles in alterations of ABCA1-mediated changes in HDL levels and atherosclerosis in response to environmental stimuli.

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)0.006
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.693
Threshold uncertainty score0.405

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
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 integrity0.0000.001
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 head0.101
GPT teacher head0.415
Teacher spread0.313 · 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

Citations22
Published2005
Admission routes1
Has abstractyes

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