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Record W2099477301 · doi:10.1002/sita.200400050

Reactivation of cardiomyocyte cell cycle: A potential approach for myocardial regeneration

2005· article· en· W2099477301 on OpenAlexafffund
Nichole McMullen, Gerard J. Gaspard, Kishore B.S. Pasumarthi

Bibliographic record

VenueSignal Transduction · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCongenital heart defects research
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health ResearchFondation pour la Recherche MédicaleResearch Nova ScotiaNova Scotia Health Research FoundationDalhousie Medical Research Foundation
KeywordsRegeneration (biology)MyocyteCell cycleZebrafishCell biologyCardiac myocyteBiologyCellCardiac function curveCardiac cycleHeart diseaseMammalian heartInternal medicineHeart failureCardiologyMedicineBiochemistry

Abstract

fetched live from OpenAlex

Abstract Regulation of cardiomyocyte cell cycle appears to be more complex in mammals compared to the lower vertebrates. Cardiomyocytes from the adult newt and zebrafish can proliferate in response to myocardial injury and regenerate the damaged area. In contrast, cardiomyocytes in the mammalian heart cease to proliferate soon after birth. This limits the ability of the mammalian heart to regenerate the damaged myocardium following heart disease. It is believed that increasing the number of myocytes in a diseased heart can decrease scar formation and improve myocardial function. To this end, reactivation of cell cycle in the surviving myocardium may have therapeutic value in the treatment of heart disease. Here we provide a summary of studies describing myocyte cell cycle activity during development and disease, mechanisms of cell cycle exit in the adult heart and genetic modulations affecting cardiomyocyte cell cycle activity. Further, we discuss the potential utility of myocyte cell cycle reactivation in cardiac regeneration as well as improvement of myocardial function.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.000

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 head0.011
GPT teacher head0.250
Teacher spread0.239 · 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 designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations3
Published2005
Admission routes2
Has abstractyes

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