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Cardiac Revascularization Post Myocardial Infarction Enhances Remuscularization and Improves Function

2020· article· en· W3016619663 on OpenAlexaffabout
Sara Nunes Vasconcelos

Bibliographic record

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicTissue Engineering and Regenerative Medicine
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsMedicineCardiologyTransplantationRevascularizationMyocardial infarctionInternal medicinePerfusionLigationIschemiaCardiac function curveHeart failure

Abstract

fetched live from OpenAlex

Background Human induced pluripotent stem cell‐derived cardiomyocytes (hiPSC‐CMs) offer an unprecedented opportunity to remuscularize infarcted human hearts. However, studies show that the majority of hiPSC‐CMs die post transplantation into the ischemic environment, limiting their regenerative potential and clinical application. Death of transplanted CMs occurs in the first few days post‐transplantation due to ischemia. Thus, attempts have been made to promote blood perfusion (i.e. addition of endothelial cells and/or angiogenic factors). However, these approaches require weeks for new vessels to form and to carry blood compared to the rapid death of transplanted CMs (2–3 days). Purpose Our goal was to improve the vascularization of the ischemic hearts to improve the survival of hiPSC‐CMs and increase heart remuscularization and function. Methods We performed left anterior descending artery (LAD) ligation in immunocompromised rats to model myocardial infarction. To improve vascularization, we used an innovative strategy consisting of ready‐made microvessels isolated from adipose tissue that form a vasculature and carry blood within the first days post subcutaneous implantation. We have co‐implanted ready‐made microvessels with hiPSC‐CMs by intra‐myocardial injection 2 weeks post LAD ligation. Cardiac function was assessed at 0, 2 and 4 weeks post‐implantation by echocardiography and by pressure‐volume loop at the endpoint (4 weeks). Immunohistochemistry and blood perfusion studies were performed at 1 and 4 weeks post‐implantation. Results Compared to hiPSC‐CM transplantation alone, microvessels promoted a ~600% increase in hiPSC‐CM survival with significant reduction in scar size. Echocardiography and pressure–volume (PV) loop analysis performed 4 weeks post‐MI revealed that hiPSC‐CM transplantation attenuated post‐infarct ventricular dilation and enhanced left ventricular contractility by demonstrating a significant improvement in fractional shortening (FS), ejection fraction (EF) as well as other functional parameters (end‐systolic volume, end‐diastolic volume, dP/dt max and min, Tau). Remarkably, co‐transplantation of hiPSC‐CMs with microvessels showed significantly superior functional recovery compared to hiPSC‐CMs alone in all the parameters assessed. Microvessels showed remarkable persistence and integration at both early and late time points, resulting in significantly faster blood perfusion and higher vessel density in the grafts. Conclusion These findings provide a novel approach to cell‐based therapies for myocardial infarction whereby incorporation of ready‐made microvessels can serve as a personalized delivery system to improve functional outcomes in cell replacement therapies post‐myocardial infarction. Support or Funding Information Canadian Institutes of Health Research (CIHR), Institute of Circulatory and Respiratory Health grant #137352 and #PJT153160. Discovery grant from the Natural Sciences and Engineering Research Council (NESERC): RGPIN 06621‐2017.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

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 integrity0.0000.000
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 head0.009
GPT teacher head0.217
Teacher spread0.208 · 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 designBench or experimental
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".

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Citations1
Published2020
Admission routes2
Has abstractyes

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