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Record W2954540379 · doi:10.1111/nyas.14123

The apelinergic system: a perspective on challenges and opportunities in cardiovascular and metabolic disorders

2019· review· en· W2954540379 on OpenAlexafffund
Éric Marsault, Catherine Llorens‐Cortés, Xavier Iturrioz, Hyung J. Chun, Olivier Lesur, Gavin Y. Oudit, Mannix Auger‐Messier

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2019
Typereview
Languageen
FieldMedicine
TopicApelin-related biomedical research
Canadian institutionsUniversity of AlbertaUniversité de Sherbrooke
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchNational Heart, Lung, and Blood InstituteHeart and Stroke Foundation of CanadaInstitut National de la Santé et de la Recherche MédicaleAmerican Heart AssociationAgence Nationale de la RechercheNational Institutes of HealthNational Science Foundation
KeywordsMedicineCrosstalkIntensive care medicineSeptic shockPerspective (graphical)BioinformaticsNeurosciencePsychologyInternal medicineBiologyComputer scienceSepsis

Abstract

fetched live from OpenAlex

The apelinergic pathway has been generating increasing interest in the past few years for its potential as a therapeutic target in several conditions associated with the cardiovascular and metabolic systems. Indeed, preclinical and, more recently, clinical evidence both point to this G protein-coupled receptor as a target of interest in the treatment of not only cardiovascular disorders such as heart failure, pulmonary arterial hypertension, atherosclerosis, or septic shock, but also of additional conditions such as water retention/hyponatremic disorders, type 2 diabetes, and preeclampsia. While it is a peculiar system with its two classes of endogenous ligand, the apelins and Elabela, its intricacies are a matter of continuing investigation to finely pinpoint its potential and how it enables crosstalk between the vasculature and organ systems of interest. In this perspective article, we first review the current knowledge on the role of the apelinergic pathway in the above systems, as well as the associated therapeutic indications and existing pharmacological tools. We also offer a perspective on the challenges and potential ahead to advance the apelinergic system as a target for therapeutic intervention in several key areas.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.973
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.308
GPT teacher head0.426
Teacher spread0.118 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations60
Published2019
Admission routes2
Has abstractyes

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