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Peroxisome proliferator activated receptors, inflammation, the vasculature and the heart

2003· book-chapter· en· W127721782 on OpenAlexaff
Quy N. Diep, Farhad Amiri, Ernesto L. Schiffrin

Bibliographic record

VenueBirkhäuser Basel eBooks · 2003
Typebook-chapter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPeroxisome Proliferator-Activated Receptors
Canadian institutionsMontreal Clinical Research Institute
Fundersnot available
KeywordsPeroxisome proliferator-activated receptorInflammationTranscription factorReceptorBiologyPeroxisomeNuclear receptorCell biologyPPAR agonistImmunologyGeneBiochemistry

Abstract

fetched live from OpenAlex

Over the last dozen years since the discovery of the family of transcription factor termed peroxisome proliferator activated receptors (PPAR) [], an impressive number of studies have investigated the characteristics, ligands and functional roles as well as molecular mechanisms of PPARs. Although PPARs were formerly believed to regulate genes involved only in lipid and glucose metabolism, a large number of more recent studies have explored the role of PPARs in cell growth, cell migration as well as in inflammation. The function of PPARs in inflammation was first demonstrated by Devchand et al. [] who showed that pro-inflammatory eicosanoid leukotriene B4 binds to PPARa and induces transcription of genes involved in wand (3-oxidation. In this chapter, we briefly summarize the role of PPARs in inflammation generally, and discuss in greater detail the role of PPARs in the heart. We will discuss molecular, biochemical, physiological and pharmacological roles of PPARa and PPARy in the regulation of cardiac hypertrophy, inflammation and cardiac function, and introduce novel concepts relating to PPARs as transcription factors in the regulation of the expression of inflammatory response genes as mechanisms that participate in the pathophysiology of cardiac 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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.588
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.008
GPT teacher head0.205
Teacher spread0.197 · 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 designBench or experimental
Domainnot available
GenreOther

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

Citations0
Published2003
Admission routes1
Has abstractyes

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