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Record W2299598005 · doi:10.1016/j.molmet.2016.03.001

High density lipoprotein and metabolic disease: Potential benefits of restoring its functional properties

2016· review· en· W2299598005 on OpenAlex
Teja Klančič, Lavinia Woodward, Susanna M. Hofmann, Edward A. Fisher

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

VenueMolecular Metabolism · 2016
Typereview
Languageen
FieldMedicine
TopicDiabetes, Cardiovascular Risks, and Lipoproteins
Canadian institutionsUniversity of Calgary
FundersNational Institutes of HealthDeutsche ForschungsgemeinschaftHelmholtz-Gemeinschaft
KeywordsMedicineMetabolic syndromeDiseaseInsulin resistanceDiabetes mellitusBioinformaticsAntithromboticInternal medicineEndocrinologyBiology

Abstract

fetched live from OpenAlex

BACKGROUND: High density lipoproteins (HDLs) are thought to be atheroprotective and to reduce the risk of cardiovascular disease (CVD). Besides their antioxidant, antithrombotic, anti-inflammatory, anti-apoptotic properties in the vasculature, HDLs also improve glucose metabolism in skeletal muscle. SCOPE OF THE REVIEW: Herein, we review the functional role of HDLs to improve metabolic disorders, especially those involving insulin resistance and to induce regression of CVD with a particular focus on current pharmacological treatment options as well as lifestyle interventions, particularly exercise. MAJOR CONCLUSIONS: Functional properties of HDLs continue to be considered important mediators to reverse metabolic dysfunction and to regress atherosclerotic cardiovascular disease. Lifestyle changes are often recommended to reduce the risk of CVD, with exercise being one of the most important of these. Understanding how exercise improves HDL function will likely lead to new approaches to battle the expanding burden of obesity and the metabolic syndrome.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.000
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 head0.030
GPT teacher head0.245
Teacher spread0.215 · 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