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Record W1491620417 · doi:10.1159/000360568

Potential Peptides in Atherosclerosis Therapy

2014· review· en· W1491620417 on OpenAlexafffund
Sylvie Marleau, Katia Mellal, David Huynh, Huy Ong

Bibliographic record

VenueFrontiers of hormone research · 2014
Typereview
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsDyslipidemiaMedicineScavenger receptorMacrophageMyocardial infarctionDiseaseAtherosclerotic cardiovascular diseaseStroke (engine)InflammationCholesterolLipid metabolismLipoproteinInternal medicineBioinformaticsImmunologyBiology

Abstract

fetched live from OpenAlex

Atherosclerosis is the main underlying cause of ischemic heart disease and related acute cardiovascular complications, including myocardial infarction and stroke. In view of the failure of statins to demonstrate a beneficial effect in all patients, exhaustive research efforts have unfold into different research avenues, in close relation to the increase in basic knowledge regarding lipoprotein metabolism, macrophage function and inflammatory conditions associated with atherosclerosis. This review focuses specifically on potential therapeutic peptides targeting dyslipidemia, macrophage scavenger receptors, cholesterol metabolism and anti-inflammatory cytokines as novel therapeutic avenues in atherosclerosis.

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)0.005
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.899
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.104
GPT teacher head0.405
Teacher spread0.301 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations10
Published2014
Admission routes2
Has abstractyes

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