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Record W4386167289 · doi:10.1038/s41536-023-00321-3

Combination human umbilical cord perivascular and endothelial colony forming cell therapy for ischemic cardiac injury

2023· article· en· W4386167289 on OpenAlexafffund
Farwah Iqbal, Alexander Johnston, Brandon A. Wyse, R. Rabani, Poonam Mander, Banafshe Hoseini, Jun Wu, Ren‐Ke Li, Andrée Gauthier-Fisher, Péter Száraz, Clifford Librach

Bibliographic record

Venuenpj Regenerative Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicTissue Engineering and Regenerative Medicine
Canadian institutionsWomen's College HospitalUniversity of TorontoUniversity Health NetworkCReATe Fertility Centre
FundersUniversity of Toronto
KeywordsUmbilical cordMedicineIschemic injuryCardiologyRescue therapyIschemiaInternal medicineAnatomy

Abstract

fetched live from OpenAlex

Cell-based therapeutics are promising interventions to repair ischemic cardiac tissue. However, no single cell type has yet been found to be both specialized and versatile enough to heal the heart. The synergistic effects of two regenerative cell types including endothelial colony forming cells (ECFC) and first-trimester human umbilical cord perivascular cells (FTM HUCPVC) with endothelial cell and pericyte properties respectively, on angiogenic and regenerative properties were tested in a rat model of myocardial infarction (MI), in vitro tube formation and Matrigel plug assay. The combination of FTM HUCPVCs and ECFCs synergistically reduced fibrosis and cardiomyocyte apoptosis, while promoting favorable cardiac remodeling and contractility. These effects were in part mediated by ANGPT2, PDGF-β, and VEGF-C. PDGF-β signaling-dependent synergistic effects on angiogenesis were also observed in vitro and in vivo. FTM HUCPVCs and ECFCs represent a cell combination therapy for promoting and sustaining vascularization following ischemic cardiac injury.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.245
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.029
GPT teacher head0.320
Teacher spread0.291 · 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 teacher head, not a consensus.

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".

Quick stats

Citations9
Published2023
Admission routes2
Has abstractyes

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