In cardiac tissue engineering cells are seeded within porous biomaterial scaffolds to create functional cardiac patches. Here, we report on a bottom-up approach to assemble a modular tissue consisting of multiple layers with distinct structures and functions. Albumin electrospun fiber scaffolds were laser-patterned to create microgrooves for engineering aligned cardiac tissues exhibiting anisotropic electrical signal propagation. Microchannels were patterned within the scaffolds and seeded with endothelial cells to form closed lumens. Moreover, cage-like structures were patterned within the scaffolds and accommodated poly(lactic-co-glycolic acid) (PLGA) microparticulate systems that controlled the release of VEGF, which promotes vascularization, or dexamethasone, an anti-inflammatory agent. The structure, morphology, and function of each layer were characterized, and the tissue layers were grown separately in their optimal conditions. Before transplantation the tissue and microparticulate layers were integrated by an ECM-based biological glue to form thick 3D cardiac patches. Finally, the patches were transplanted in rats, and their vascularization was assessed. Because of the simple modularity of this approach, we believe that it could be used in the future to assemble other multicellular, thick, 3D, functional tissues.
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http://dx.doi.org/10.1073/pnas.1615728114 | DOI Listing |
Acta Physiol (Oxf)
February 2025
Department of Biochemistry, Cell and Systems Biology, Institute of Systems, Molecular and Integrative Biology, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UK.
Aim: Long QT syndrome (LQTS) and catecholaminergic polymorphism ventricular tachycardia (CPVT) are inherited cardiac disorders often caused by mutations in ion channels. These arrhythmia syndromes have recently been associated with calmodulin (CaM) variants. Here, we investigate the impact of the arrhythmogenic variants D131E and Q135P on CaM's structure-function relationship.
View Article and Find Full Text PDFNeural Netw
January 2025
Tsinghua University, Beijing, China. Electronic address:
Artificial neural networks (ANNs) can help camera-based remote photoplethysmography (rPPG) in measuring cardiac activity and physiological signals from facial videos, such as pulse wave, heart rate and respiration rate with better accuracy. However, most existing ANN-based methods require substantial computing resources, which poses challenges for effective deployment on mobile devices. Spiking neural networks (SNNs), on the other hand, hold immense potential for energy-efficient deep learning owing to their binary and event-driven architecture.
View Article and Find Full Text PDFCephalalgia
January 2025
Department of Pharmacology, University of Arizona College of Medicine, Tucson, AZ, USA.
Background: Women with endometriosis are more likely to have migraine. The mechanisms underlying this co-morbidity are unknown. Prolactin, a neurohormone secreted and released into circulation from the anterior pituitary, can sensitize sensory neurons from female, but not male, rodents, monkeys and human donors.
View Article and Find Full Text PDFBioact Mater
April 2025
School of Medicine South China University of Technology, Guangzhou, Guangdong, 510006, China.
The cardiac microenvironment profoundly restricts the efficacy of myocardial regeneration tactics for the treatment of myocardial infarction (MI). A prospective approach for MI therapeutics encompasses the combined strategy of scavenging reactive oxygen species (ROS) to alleviate oxidative stress injury and facilitating macrophage polarization towards the regenerative M2 phenotype. In this investigation, we fabricated a ROS-sensitive hydrogel engineered to deliver our previously engineered IL-1β-VHH for myocardial restoration.
View Article and Find Full Text PDFEur Heart J Imaging Methods Pract
January 2025
Department of Cardiovascular Medicine, Faculty of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan.
Aims: Amyloid deposition in myocardial tissue is a definitive feature for diagnosing cardiac amyloidosis, though less invasive imaging modalities such as bone tracer cardiac scintigraphy and cardiac magnetic resonance imaging have been established as first steps for its diagnosis. This study aimed to develop a deep learning model to support the diagnosis of cardiac amyloidosis from haematoxylin/eosin (HE)-stained myocardial tissue.
Methods And Results: This single-centre retrospective observational study enrolled 166 patients who underwent myocardial biopsies between 2008 and 2022, including 76 patients diagnosed with cardiac amyloidosis and 90 with other diagnoses.
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