Publications

Duchenne muscular dystrophy (DMD) is the most prevalent neuromuscular disease diagnosed in childhood. It is a progressive and wasting disease, characterized by a degeneration of skeletal and cardiac muscles caused by the lack of dystrophin protein. The absence of this crucial structural protein leads to sarcolemmal fragility, resulting in muscle fiber damage during contraction. Despite ongoing efforts, there is no cure available for DMD patients. One of the primary challenges is the limited efficacy of current preclinical tools, which fail in modeling the biological complexity of the disease. Human-based three-dimensional (3D) cell culture methods appear as a novel approach to accelerate preclinical research by enhancing the reproduction of pathophysiological processes in skeletal muscle. In this work, we developed a patient-derived functional 3D skeletal muscle model of DMD that reproduces the sarcolemmal damage found in the native DMD muscle. These bioengineered skeletal muscle tissues exhibit contractile functionality, as they responded to electrical pulse stimulation. Sustained contractile regimes induced the loss of myotube integrity, mirroring the pathological myotube breakdown inherent in DMD due to sarcolemmal instability. Moreover, damaged DMD tissues showed disease functional phenotypes, such as tetanic fatigue. We also evaluated the therapeutic effect of utrophin upregulator drug candidates on the functionality of the skeletal muscle tissues, thus providing deeper insight into the real impact of these treatments. Overall, our findings underscore the potential of bioengineered 3D skeletal muscle technology to advance DMD research and facilitate the development of novel therapies for DMD and related neuromuscular disorders.

JTD Keywords: 3d cell culture, disease modeling, drug testing, duchenne muscular dystrophy, sarcolemmal damage, skeletal muscle, 3d cell culture, Animal-models, Disease modeling, Dmso, Drug testing, Duchenne muscular dystrophy, Gene, Humans, Image, Mechanisms, Muscle fibers, skeletal, Muscle, skeletal, Muscular dystrophy, duchenne, Myocardium, Sarcolemmal damage, Skeletal muscle, Tissue engineering, Utrophin

The creation of cardiac tissue models for preclinical testing is still a non-solved problem in drug discovery, due to the limitations related to thein vitroreplication of cardiac tissue complexity. Among these limitations, the difficulty of mimicking the functional properties of the myocardium due to the immaturity of the used cells hampers the obtention of reliable results that could be translated into human patients.In vivomodels are the current gold standard to test new treatments, although it is widely acknowledged that the used animals are unable to fully recapitulate human physiology, which often leads to failures during clinical trials. In the present work, we present a microfluidic platform that aims to provide a range of signaling cues to immature cardiac cells to drive them towards an adult phenotype. The device combines topographical electrospun nanofibers with electrical stimulation in a microfabricated system. We validated our platform using a co-culture of neonatal mouse cardiomyocytes and cardiac fibroblasts, showing that it allows us to control the degree of anisotropy of the cardiac tissue inside the microdevice in a cost-effective way. Moreover, a 3D computational model of the electrical field was created and validated to demonstrate that our platform is able to closely match the distribution obtained with the gold standard (planar electrode technology) using inexpensive rod-shaped biocompatible stainless-steel electrodes. The functionality of the electrical stimulation was shown to induce a higher expression of the tight junction protein Cx-43, as well as the upregulation of several key genes involved in conductive and structural cardiac properties. These results validate our platform as a powerful tool for the tissue engineering community due to its low cost, high imaging compatibility, versatility, and high-throughput configuration capabilities.

JTD Keywords: bioreactor, cardiac tissue engineering, cardiomyocytes, electrospinning, fabrication, fibroblasts, heart-on-a-chip, heart-tissue, in vitro models, myocardium, orientation, platform, scaffolds, Cardiac tissue engineering, Electrospinning, Field stimulation, Heart-on-a-chip, In vitro models, Microphysiological system

Ischemic and dilated cardiomyopathy are associated with disorders of myocardium. Using the blood pressure (BP) signal and the values of the ventricular ejection fraction, we obtained parameters for stratifying cardiomyopathy patients as low- and high-risk. We studied 48 cardiomyopathy patients characterized by NYHA ≥2: 19 patients with dilated cardiomyopathy (DCM) and 29 patients with ischemic cardiomyopathy (ICM). The left ventricular ejection fraction (LVEF) percentage was used to classify patients in low risk (LR: LVEF > 35%, 17 patients) and high risk (HR: LVEF ≤ 35%, 31 patients) groups. From the BP signal, we extracted the upward systolic slope (BP_sl), the difference between systolic and diastolic BP (BPA), and systolic time intervals (STI). When we compared the LR and HR groups in the time domain analysis, the best parameters were standard deviation (SD) of 1=STI, kurtosis (K) of BP_sl, and K of BPA. In the frequency domain analysis, very low frequency (VLF) and high frequency (HF) bands showed statistically significant differences in comaprisons of LR and HR groups. The area under the curve of power spectral density was the best parameter in all classifications, and particularly in the very-low-and high- frequency bands (p <; 0.001). These parameters could help to improve the risk stratification of cardiomyopathy patients.

JTD Keywords: blood pressure measurement, cardiovascular system, diseases, medical disorders, medical signal processing, statistical analysis, time-domain analysis, BP signal, HR groups, LR groups, blood pressure signal analysis, cardiomyopathy patients, diastolic BP, dilated cardiomyopathy, frequency domain analysis, high-frequency bands, ischemic cardiomyopathy, left ventricular ejection fraction, low-frequency bands, myocardium disorders, patient characterization, power spectral density curve, standard deviation, statistical significant differences, systolic BP, systolic slope, systolic time intervals, time domain analysis, ventricular ejection fraction, Abstracts, Databases, Parameter extraction, Telecommunication standards, Time-frequency analysis