Nanoscale Technologies for Prevention and Treatment of Heart Failure: Challenges and Opportunities

Abstract

The adult myocardium has a limited regenerative capacity following heart injury, and the lost cells are primarily replaced by fibrotic scar tissue. Suboptimal efficiency of current clinical therapies to resurrect the infarcted heart results in injured heart enlargement and remodeling to maintain its physiological functions. These remodeling processes ultimately leads to ischemic cardiomyopathy and heart failure (HF). Recent therapeutic approaches (e.g., regenerative and nanomedicine) have shown promise to prevent HF postmyocardial infarction in animal models. However, these preclinical, clinical, and technological advancements have yet to yield substantial enhancements in the survival rate and quality of life of patients with severe ischemic injuries. This could be attributed largely to the considerable gap in knowledge between clinicians and nanobioengineers. Development of highly effective cardiac regenerative therapies requires connecting and coordinating multiple fields, including cardiology, cellular and molecular biology, biochemistry and chemistry, and mechanical and materials sciences, among others. This review is particularly intended to bridge the knowledge gap between cardiologists and regenerative nanomedicine experts. Establishing this multidisciplinary knowledge base may help pave the way for developing novel, safer, and more effective approaches that will enable the medical community to reduce morbidity and mortality in HF patients.

Figure 1.

Scheme showing the shielding effect of protein corona on targeted nanoparticles according to their characteristics. Figures are reproduced from the reference; copyright [2011] e-Century Publishing Corporation.

Figure 2.

Schematic showing the proposed strategies to minimize the shielding effects of the biomolecular/protein corona through (A) use of specific coatings to diminish biomolecular attachment to the surface of nanoparticles, (B) pre-coating, and (C) pre-adsorption of targeting species, rather than chemical conjugation, to the surface of nanoparticles. Figures are reproduced from the reference; copyright [2018] Nature Publishing Group.

Figure 3.

Using protein corona sensor array for identification and discrimination of cancers at various stages. (A) Outcomes of the supervised classifier projecting cancers into the subspace created by the 1st, 2nd, and 3rd latent variables of the classifier. (B) Two types of brain cancers were discriminated in 4th and 5th latent variables of the model. (C), (D) Successful classification of cancers in plasma samples from healthy individuals who developed lung, brain, and pancreatic cancers eight years after plasma collections in the 1st and 2nd latent variables of the two developed models. Figures are reproduced from the reference; copyright [2019] The Royal Society of Chemistry.

Figure 4.

Schematic representation of myocardial infarction–specific biomarkers

Figure 5.

Development of thermo-responsive polymeric nanoplatforms with embedded superparamagnetic iron oxide nanoparticles. The superparamagnetic iron oxide nanoparticles can be heated using an external magnetic field, which activates the thermo-responsive polymeric carrier to release the payload. Figure is reproduced from reference; copyright [2011] Elsevier.

Figure 6.

Flow cytometry results demonstrating the uptake of protein corona coated liposomes [with positive (red), neutral (green) and negative (blue) surface charges], after incubation with various concentrations of human plasma (HP), by human monocyte THP-1 cells. (B) Uptake of various corona coated liposomes by distinct leukocyte subpopulations. Figures are reproduced from the reference; copyright [2019] Nature Publishing Group.

Figure 7.

(A) Schematic showing high-density and safe loading of iron oxide nanoparticles in therapeutic cells using biodegradable poly(lactide-co-glycolide) microparticles. Transmission electron microscopy images of the labeled cells with (B) magnetic nanoparticles embedded in microcapsules (PLGA-MPs) and (C) magnetic nanoparticles alone (IO-NPs) are shown. White, blue, and red arrows show the locations of IO-NPs, PLGA-MPs, and membrane of intracellular compartment, respectively. The results demonstrate the superior role of microparticles in (D) labeling the cells at various times (according to the cellular iron content) and (E) maintenance of the loaded iron ions in the cells. (F) R2-weighted MR images of equivalent numbers of labeled and unlabeled cells show the higher magnetization of microparticle-labeled cells over nanoparticles alone. (G) Fluorescent confocal image of the labeled cells with microparticles (18 days after labeling) (Green: cell membrane; Blue: nucleus Red: microparticles); scale bar is 10 μm. Figures B and G were reproduced from ref; copyright [2012] American Chemical Society.

Figure 8.

(A) Gold nanorods adsorption to albumin electrospun fiber scaffolds. (B) Cardiac cells are seeded within the nanocomposite scaffolds to form the (C) cardiac patch. (D) Mechanism of cardiac patch integration. (E) The cardiac patch after integration with the rat heart. Figures are reproduced from the reference; copyright [2018] American Chemical Society.

Figure 9:

Bioluminescence and magnetic resonance images of the mice injected with therapeutic cells, labelled with a live contrast agent (ME) or synthetic iron oxide nanoparticles (Molday). Arrows show the signal from the injected cells; two weeks after therapeutic cell injection, the arrows show the persisted signal in Molday-labeled cells, whereas the absence of bioluminescence signal confirmed the absence of live therapeutic cells in the area. Figures are reproduced from the reference; copyright [2016] Nature Publishing Group.

Figure 10.

Substrates with the physiological stiffness and two-dimensional shape of cardiomyocytes show a unique capacity in inducing maturation in hiPSC-derived cardiomyocytes. The cultured hiPSC-derived cardiomyocytes on the patterned substrates demonstrated isotropic (A) calcium flow (green) and (B) mitochondria distribution (green) compared to unpatterned substrates. (C) Variation of patch-clamp recordings (left) and action potential amplitude (right) of the cells cultured on patterned and unpatterned substrates. (D) Single-cell gene expression outcomes show an excellent ability of patterned substrates to induce gene maturation. (E) Directed distribution of t-tubule–like structures along the cell membrane of the cultured immature cells on patterned and unpatterned substrates. Figures are reproduced from the reference; copyright [2015] National Academy of Sciences.

Figure 11.

(A) Scheme showing the preparation of patterned substrates based on the 3D- cardiomyocytes’ shapes (cylindrical), and the scanning electron microscopy images showing the formation of patterned substrates. (B) Confocal images of the culture (at day 14) of the immature hiPSC-derived cardiomyocytes on the aligned patterned substrates with the shape of mature cardiomyocytes at different magnifications. As can be clearly seen in these images and the analyzed cell- and nucleus-alignment pies, the cultured cells on the patterned substrate induced the shape of cardiomyocytes and their nuclei (ellipsoidal shape) to the cultured cells in an aligned format; the cultured cells on the smooth substrate at the same age are presented for comparison (lower left panel). Figures are reproduced from reference; copyright [2018] Wiley-VCH.

Figure 12.

Schematic showing examples of stimuli-responsive nanoparticles: the capacity of H₂O₂-responsive copolyoxalate polymeric nanoparticles to release their loaded drug (vanillyl alcohol; green dots) upon exposure to H₂O_2.

Figure 13:

The minimum set of required information and experimental setups that should be mentioned in nanomedicine related reports to achieve robust and reliable nanomedicine readouts. The figure was reproduced from the reference; copyright [2018] Cell Press.

Figure 14.

(A) Variation of model nanoparticle (i.e., QDs) uptake in female and male human amniotic mesenchymal stem cells. (B) Differences in organization, distribution, and morphology of actin filaments/bundles in the cytoplasm of the male and female cells using super-resolution microscopy (scale bar: 1 μm). (C) Flow cytometry analysis demonstrating differences of reprogramming efficiency of male and female human amniotic mesenchymal stem cells (top panels) toward human pluripotent stem cells and the number of the reprogrammed colonies in culture (bottom panels). Figures are reproduced from the reference; copyright [2018] American Chemical Society.