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Record W2060096807 · doi:10.4061/2011/836806

Postmyocardial Infarct Remodeling and Heart Failure: Potential Contributions from Pro- and Antiaging Factors

2011· article· en· W2060096807 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCardiology Research and Practice · 2011
Typearticle
Languageen
FieldMedicine
TopicTissue Engineering and Regenerative Medicine
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineMyocardial infarctionVentricular remodelingStem cellHeart failureInternal medicineCardiologyRegeneration (biology)BioinformaticsBiologyCell biology

Abstract

fetched live from OpenAlex

Myocardial infarction and adverse postinfarct remodeling in older persons lead to poor outcome and need greater understanding of the contributions of age-related factors on abnormal cardiac function and management. In this perspective, how normal aging processes could contribute to the events of post-myocardial infarction and remodeling is reviewed. Post-myocardial infarction and remodeling involve cardiomechanical factors and neurohormonal response. Many factors prevent or accelerate aging including immunosenescence, recruitment and regeneration of stem cells, telomere shortening, oxidative damage, antiaging hormones klotho and melatonin, nutrition, and Sirtiun protein family, and these factors could affect post-MI remodeling and heart failure. Interest in stem cell repair of myocardial infarcts to mitigate post-MI remodeling needs more information on aging of stem cells, and potential effects on stem cell use in infarct repair. Integrating genomics and proteomics methods may help find clinically novel therapy in the management of post-MI remodeling and heart failure in aged individuals.

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.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.716
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.098
GPT teacher head0.382
Teacher spread0.284 · 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