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Record W2984927527 · doi:10.1007/978-3-030-31261-9_9

Therapeutic Use of Bioengineered Materials for Myocardial Infarction

2019· book-chapter· en· W2984927527 on OpenAlexaff
Veronika Sedláková, Marc Ruel, Erik J. Suuronen

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMedicine
TopicTissue Engineering and Regenerative Medicine
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMyocardial infarctionMedicineHeart failureExtracellular matrixVentricular remodelingCardiologyIntensive care medicineCell biologyBiology

Abstract

fetched live from OpenAlex

Cardiovascular disease is a leading cause of worldwide mortality. Despite the success of current therapies for acute myocardial infarction (MI), many patients still suffer irreversible damage, and the prevalence of heart failure is growing. After MI, the extracellular matrix (ECM) of the damaged myocardium is modified to produce scar tissue. This remodeling reduces the efficacy of therapies and also hinders endogenous repair mechanisms. Therefore, a strategy to prevent adverse remodeling and provide a suitable ECM environment that supports cells, tissue repair and functional restoration may lead to a superior therapeutic outcome in MI patients. Bioengineered materials are an attractive approach for achieving this. Herein, we review current research on materials that can act as a biomimetic matrix for supporting cellular repair in the post-MI heart. We also examine how nanomaterials are being used to treat the damaged heart. Finally, we provide an overview of the breakthroughs and limitations of biomaterial therapies for cardiac repair.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.940
Threshold uncertainty score0.769

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.047
GPT teacher head0.265
Teacher spread0.217 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations8
Published2019
Admission routes1
Has abstractyes

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