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Record W2133082213 · doi:10.1093/hmg/ddm170

Cholesterol biosynthesis pathway is disturbed in YAC128 mice and is modulated by huntingtin mutation

2007· article· en· W2133082213 on OpenAlexaff
Marta Valenza, Jeffrey B. Carroll, Valerio Leoni, L Bertram, Ingemar Björkhem, Roshni R. Singaraja, Stefano Di Donato, Dieter Lütjohann, Michael R. Hayden, Elena Cattaneo

Bibliographic record

VenueHuman Molecular Genetics · 2007
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHuntingtinBiologyMutationBiosynthesisGeneticsCholesterolCell biologyGeneBiochemistryMutant

Abstract

fetched live from OpenAlex

Our recent analyses of the cholesterol biosynthetic pathway in Huntington's disease (HD) cells, in the R6/2 huntingtin-fragment mouse model of HD as well as in human tissues have provided the first evidence of altered activity of this pathway in genetically identifiable HD samples. Here we report that these changes also occur in the full-length-huntingtin YAC128 (yeast artificial chromosome) mouse model, which shows a consistent reduction in the activity or levels of multiple components of the cholesterogenic pathway. We also show that this phenotype is progressive and is specific for the brain region most affected in HD. Mice over-expressing the wild-type protein with 18 CAG (YAC18 mice) show the opposite phenotype with higher activity of the cholesterol biosynthetic pathway compared with littermate mice. Finally, we report that plasma levels of cholesterol, its precursors and its brain-derived catabolite 24-S-hydroxycholesterol in YAC mice mirror brain biosynthetic levels supporting further investigation of their potential as peripheral biomarkers in HD.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.016
GPT teacher head0.263
Teacher spread0.246 · 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 source (direct Gemma or distilled Codex), 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

Citations126
Published2007
Admission routes1
Has abstractyes

Explore more

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