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Loss of γ-Secretase Function Impairs Endocytosis of Lipoprotein Particles and Membrane Cholesterol Homeostasis

2008· article· en· W2050989831 on OpenAlexaff
Irfan Y. Tamboli, Kai Prager, Dietmar Rudolf Thal, Karin Thelen, Ilse Dewachter, Claus U. Pietrzik, Peter St George‐Hyslop, Sangram S. Sisodia, Bart De Strooper, Michael T. Heneka, Mikhail A Filippov, Ulrike Müller, Fred Van Leuven, Dieter Lütjohann, Jochen Walter

Bibliographic record

VenueJournal of Neuroscience · 2008
Typearticle
Languageen
FieldMedicine
TopicCholesterol and Lipid Metabolism
Canadian institutionsUniversity of Toronto
FundersRheinische Friedrich-Wilhelms-Universität BonnBundesministerium für Bildung und ForschungDeutsche ForschungsgemeinschaftWellcome Trust
KeywordsEndocytosisLDL receptorCell biologyLRP1BiologyDownregulation and upregulationApolipoprotein EPresenilinAmyloid precursor protein secretaseReceptorEndocytic cycleLipoproteinChemistryAmyloid precursor proteinCholesterolAlzheimer's diseaseBiochemistryInternal medicineGeneDiseaseMedicine

Abstract

fetched live from OpenAlex

Presenilins (PSs) are components of the gamma-secretase complex that mediates intramembranous cleavage of type I membrane proteins. We show that gamma-secretase is involved in the regulation of cellular lipoprotein uptake. Loss of gamma-secretase function decreased endocytosis of low-density lipoprotein (LDL) receptor. The decreased uptake of lipoproteins led to upregulation of cellular cholesterol biosynthesis by increased expression of CYP51 and enhanced metabolism of lanosterol. Genetic deletion of PS1 or transgenic expression of PS1 mutants that cause early-onset Alzheimer's disease led to accumulation of gamma-secretase substrates and mistargeting of adaptor proteins that regulate endocytosis of the LDL receptor. Consistent with decreased endocytosis of these receptors, PS1 mutant mice have elevated levels of apolipoprotein E in the brain. Thus, these data demonstrate a functional link between two major genetic factors that cause early-onset and late-onset Alzheimer's disease.

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 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 score0.640
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.031
GPT teacher head0.260
Teacher spread0.229 · 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

Citations68
Published2008
Admission routes1
Has abstractyes

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