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Record W4206446840 · doi:10.1016/j.tcm.2022.01.002

MEF2 in cardiac hypertrophy in response to hypertension

2022· review· en· W4206446840 on OpenAlexaff
James D. Cornwell, John C. McDermott

Bibliographic record

VenueTrends in Cardiovascular Medicine · 2022
Typereview
Languageen
FieldMedicine
TopicCardiac Fibrosis and Remodeling
Canadian institutionsYork University
Fundersnot available
KeywordsMef2Heart failureMuscle hypertrophyPressure overloadPathologicalCardiologyMedicineCardiac hypertrophyInternal medicineCardiac myocyteRisk factorLeft ventricular hypertrophyBlood pressureEnhancerTranscription factorBiologyGene

Abstract

fetched live from OpenAlex

Hypertension is a globally prevalent pathological condition and an underlying risk factor for the development of cardiac hypertrophy leading to heart failure. Myocyte enhancer factor 2 (Mef2) has been identified as one of the primary effectors of morphological changes in the hypertensive heart, as part of a complex network of molecular signaling controlling cardiac gene expression. Experimental chronic pressure-overload models that mimic hypertension in the mammalian heart lead to the activation of various pathological mechanisms that result in structural changes leading to debilitating cardiac hypertrophy and ultimately heart failure. The purpose here is to survey the literature implicating Mef2 in hypertension induced cardiac hypertrophy, towards illuminating points of interest for understanding and potentially treating heart failure.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.085
GPT teacher head0.341
Teacher spread0.256 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations39
Published2022
Admission routes1
Has abstractyes

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