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Record W2023801822 · doi:10.1093/cvr/cvq124

Cardiac progenitor cell sheet regenerates myocardium and renews hope for translation

2010· letter· en· W2023801822 on OpenAlexaff
Paul W.M. Fedak

Bibliographic record

VenueCardiovascular Research · 2010
Typeletter
Languageen
FieldMedicine
TopicTissue Engineering and Regenerative Medicine
Canadian institutionsLibin Cardiovascular Institute of AlbertaFoothills Medical CentreUniversity of Calgary
Fundersnot available
KeywordsProgenitor cellTransplantationRegeneration (biology)Stem cellMedicineCardiologyHeart failureCell therapyProgenitorMyocardial infarctionInternal medicineCell biologyCancer researchBiology

Abstract

fetched live from OpenAlex

This editorial refers to ‘Transplantation of cardiac progenitor cell sheet onto infarcted heart promotes cardiogenesis and improves function’ by L. Zakharova et al ., pp. 40–49, this issue. The goal of myocardial regeneration strategies is to transform dead scar tissue into viable functional muscle. If achieved, we could eradicate congestive heart failure. Early work using cell suspensions with delivery by injection showed promise, but substantial regeneration has remained elusive for our patients, mostly due to poor viability and donor cell retention after transplantation. The enthusiasm for this strategy is fading. The innovative work of Zakharova et al .1 could restore hope and help guide us in the right direction. The authors assembled cardiac progenitor cells into a tissue-like sheet of cells and then delivered the construct onto the epicardial surface of an acute rat infarction. This unique approach enhanced stem cell engraftment and survival, stimulated a substantial cardiogenesis, and preserved left ventricular function to an extent that could prevent the transition to overt heart failure. Importantly, the donor cells did more than survive in the host myocardium; after engraftment, they showed an encouraging combination of controlled proliferation, purposeful migration, and targeted differentiation. The authors then extended, confirmed, and reproduced these results using human progenitor cells obtained from surgical biopsy. The potential for translation to our patients using this strategy is exciting. Progress in using cell …

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.675
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.005
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 head0.079
GPT teacher head0.332
Teacher spread0.253 · 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; both teacher heads agree on what is shown here.

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

Citations7
Published2010
Admission routes1
Has abstractyes

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