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Record W1982717038 · doi:10.2174/13816128113199990351

Emerging Anti-inflammatory Therapies for Atherosclerosis

2013· review· en· W1982717038 on OpenAlexaff
François Roubille, Ekaterini A. Kritikou, C. Roubille, Jean‐Claude Tardif

Bibliographic record

VenueCurrent Pharmaceutical Design · 2013
Typereview
Languageen
FieldMedicine
TopicLipid metabolism and disorders
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsMedicineInflammationTumor necrosis factor alphaColchicineDiseaseImmunologyInterleukinCytokinePathologyInternal medicine

Abstract

fetched live from OpenAlex

Atherosclerosis remains one of the main causes of cardiovascular disease, which is the leading cause of death worldwide. It is now accepted that atherosclerosis is an inflammatory, dynamic and complex disease involving multiple cell types, and many antiinflammatory strategies have recently emerged as potential therapeutic approaches for atherosclerotic disease. In this review, we discuss the most recent progress in the development of anti-inflammatory strategies. We highlight the beneficial effects of potent antiinflammatory drugs, including recently developed biologics, and we describe diverse emerging approaches that target inflammatory processes involved in atherosclerosis including tumor necrosis factor antagonists, anti-interleukins, viral-derived serpins, P-selectin inhibition and leukotriene synthesis inhibition.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.973
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.276
GPT teacher head0.456
Teacher spread0.180 · 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

Citations21
Published2013
Admission routes1
Has abstractyes

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