MétaCan
Menu
Back to cohort
Record W2027308727 · doi:10.1002/iub.1091

Cholesterol and Alzheimer's disease: A still poorly understood correlation

2012· review· en· W2027308727 on OpenAlex
Roberta Ricciarelli, Elisa Canepa, Barbara Marengo, Umberto M. Marinari, Giuseppe Poli, Maria Adelaide Pronzato, Cinzia Domenicotti

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIUBMB Life · 2012
Typereview
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsTellabs (Canada)
FundersAlzheimer's Association
KeywordsCholesterolDiseaseAlzheimer's diseaseMedicineInternal medicineChemistry

Abstract

fetched live from OpenAlex

A large amount of evidence suggests a pathogenic link between cholesterol homeostasis dysregulation and Alzheimer's disease (AD). In cell culture systems, the production of amyloid-β (Aβ) is modulated by cholesterol, and studies on animal models have consistently demonstrated that hypercholesterolemia is associated with an increased deposition of cerebral Aβ peptides. Consequently, a number of epidemiological studies have examined the effects of cholesterol-lowering drugs (i.e., statins) in the prevention and the treatment of AD. However, while retrospective studies suggested a potential benefit of statin therapy, clinical trials produced inconsistent results. Here, we summarize the main findings from in vitro and in vivo research where the correlation between cholesterol and the neurodegenerative disorder was investigated. Recognition of this correlation could be an important step forward for our understanding of AD pathogenesis and, possibly, for the development of new therapeutic strategies.

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.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.961
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.118
GPT teacher head0.376
Teacher spread0.258 · 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