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Abstract 13347: Injectable Collagen-based Hydrogel Matrix Modulates Micro-RNA Expression and Prevents Cardiac Deterioration Post-myocardial Infarction

2014· article· en· W1549532704 on OpenAlexaff
Nick J. R. Blackburn, Brian McNeill, Hélène Chiarella-Redfern, Tanja Sofrenovic, Drew Kuraitis, Ali Ahmadi, Marc Ruel, Katey J. Rayner, Erik J. Suuronen

Bibliographic record

VenueCirculation · 2014
Typearticle
Languageen
FieldMedicine
TopicTissue Engineering and Regenerative Medicine
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineAngiogenesisMyocardial infarctionEjection fractionmicroRNACardiologyMatrix (chemical analysis)Cardiac function curveExtracellular matrixInternal medicineHeart failureCell biology

Abstract

fetched live from OpenAlex

Background: Injectable hydrogel biomaterials have emerged as promising therapies for treating myocardial infarction (MI). We developed a collagen type I based injectable hydrogel matrix that can prevent the deterioration of cardiac function when delivered soon post-MI and found that the effects may be mediated through a microRNA (miRNA) mechanism. Methods/Results: C57BL/6J mice underwent LAD ligation to induce MI. Mice then received myocardial injections of PBS or matrix delivered at 3hours post-MI. Analyses were performed at 2 days, 1 and 3 months post-treatment. At one month post-treatment, mice that received the matrix had superior left ventricular ejection fraction (LVEF; 45.1±2.3%) compared to the PBS group (29.6±2.4%; p< 0.001). LVEF was maintained in matrix-treated mice at 3 months (42.9±3.8%). Matrix treatment was also associated with reduced infarct sizes and improved ventricular volumes. Matrix-treated mice had more angiogenesis, mitigated apoptosis and reduced inflammation in the infarcted myocardium at both 2 and 28 days post-treatment. To better understand the mechanisms, we performed miRNA microarrays on infarct and peri-infarct tissue. Matrix treatment resulted in 120 miRNAs with differential expression within +/- 0.3 log2 fold change. In particular, we found matrix treatment down-regulated miR-92a ( p< 0.0005), an anti-angiogenic miRNA. Integrins α5 (Itgα5) and αV (ItgαV), involved in angiogenesis and cell-matrix interactions, were identified as putative miR-92a targets and pursued further in vitro using circulating angiogenic cells (CACs). CACs cultured on the matrix had increased Itgα5 and ItgαV expression after 4 days (12.4-fold and 13.9-fold, respectively vs. fibronectin; p< 0.01). When applied in an in vitro angiogenesis assay, the number of CACs that incorporated into capillary-like structures was greater (by 4.2-fold) for cells derived from matrix culture ( p <0.005). Conclusion: We demonstrate pronounced benefits associated with our hydrogel matrix when delivered at 3h post-MI. The matrix effects may be mediated, at least in part, through its ability to regulate miR-92a and integrin-mechanisms. Overall, the matrix may provide a promising therapeutic approach for protecting the myocardium post-MI.

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 score0.003
Threshold uncertainty score0.010

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)0.0030.001

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 head0.008
GPT teacher head0.245
Teacher spread0.237 · 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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Citations0
Published2014
Admission routes1
Has abstractyes

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