A Systematic Review of Tissue Engineering of a Total Artificial Heart: Focus on Perfusion Decellularization
Bibliographic record
Abstract
Introduction: A leading cause of death worldwide is heart disease, and in the United States alone, 6.2 million individuals live with heart failure. The recent ability to recreate the vascular network of cardiac Extracellular Matrix (ECM) suggests the feasibility of engineering whole heart constructs. Tissue engineering method such as perfusion decellularization allows for effective removal of nearly all cellular composition of a heart while maintaining the native mechanical integrity of the scaffold. This scaffold can be reseeded with stem cells in the hopes of generating a functional heart. The goal of this systematic review was to assess the various perfusion decellularization methods and its effects upon the biologic scaffold. Methodology: A comprehensive systematic literature review search was carried out through Pubmed, MEDLINE and Google Scholar using the search terms “whole heart decellularization”, “whole organ decellularization” and “perfusion decellularization”. The inclusion criteria for this research were as follows: scholarly or peer-reviewed studies, published within the last 20 years in the English language, and primary studies in which whole cardiac organ decellularization was performed. Chosen articles were those examining the various decellularization methods and its effects upon the biologic scaffold. Excluded were studies regarding heart valve decellularization, tissue decellularization, cardiac patch, tissue recellularization, articles in foreign languages, articles dated prior to 2001, literature reviews, systematic reviews, and duplicate articles. Results: Chemical agents such as acid and bases cause hydrolytic degradation of biomolecules which could reduce ECM strength and eliminate growth factors from the matrix. Compared to other detergents such as Triton X-100, sodium dodecyl sulfate yields a more complete removal of nuclear material. A combination of these various approaches has shown an increased efficacy of the decellularization process. The decellularization of a large solid organ such as the heart requires several sophisticated steps. Perfusion decellularization is achieved via anterograde or retrograde perfusion of the intrinsic vascular network of the heart by utilizing decellularizing agents (i.e., chemicals and/or enzymes). Hodgson et al., 2017 demonstrates a combined strategy in which the decellularization of porcine hearts is accomplished in 24 hours and results in 98% DNA removal with only 6 hours of detergent exposure. Conclusion: There have been significant advances to address the heart disease epidemic. A promising approach is perfusion decellularization which allows for complete DNA content removal while maintaining the ECM scaffold integrity. This scaffold is then re-cellularized with stem cells in the hopes of creating an artificial heart. There are several challenges that need to be surpassed before bio-artificial hearts can be used to replace in vivo function. Future research is directed towards optimizing types of cells and cell sources used to repopulate decellularized hearts, seeding strategies and bioreactor systems to provide in vitro conditions required for organ maturation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.015 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".