APL Bioengineering最新文献

During cancer metastasis, cancer cells will encounter various microenvironments with diverse physical characteristics. Changes in these physical characteristics such as tension, stiffness, viscosity, compression, and fluid shear can generate biomechanical cues that affect cancer cells, dynamically influencing numerous pathophysiological mechanisms. For example, a dense extracellular matrix drives cancer cells to reorganize their cytoskeleton structures, facilitating confined migration, while this dense and restricted space also acts as a physical barrier that potentially results in nuclear rupture. Identifying these pathophysiological processes and understanding their underlying mechanobiological mechanisms can aid in the development of more effective therapeutics targeted to cancer metastasis. In this review, we outline the advances of engineering microfluidic devices in vitro and their role in replicating tumor microenvironment to mimic in vivo settings. We highlight the potential cellular mechanisms that mediate their ability to adapt to different microenvironments. Meanwhile, we also discuss some important mechanical cues that still remain challenging to replicate in current microfluidic devices in future direction. While much remains to be explored about cancer mechanobiology, we believe the developments of microfluidic devices will reveal how these physical cues impact the behaviors of cancer cells. It will be crucial in the understanding of cancer metastasis, and potentially contributing to better drug development and cancer therapy.

Tumor treating fields (TTFields) are a type of sinusoidal alternating current electric field that has proven effective in inhibiting the reproduction of dividing tumor cells. Despite their recognized impact, the precise biophysical mechanisms underlying the unique effects of TTFields remain unknown. Many of the previous studies predominantly attribute the inhibitory effects of TTFields to mitotic disruption, with intracellular microtubules identified as crucial targets. However, this conceptual framework lacks substantiation at the mesoscopic level. This study addresses the existing gap by constructing force models for tubulin and other key subcellular structures involved in microtubule electrophysiological activities under TTFields exposure. The primary objective is to explore whether the electric force or torque exerted by TTFields significantly influences the normal structure and activities of microtubules. Initially, we examine the potential effect on the dynamic stability of microtubule structures by calculating the electric field torque on the tubulin dimer orientation. Furthermore, given the importance of electrostatics in microtubule-associated activities, such as chromosome segregation and substance transport of kinesin during mitosis, we investigate the interaction between TTFields and these electrostatic processes. Our data show that the electrodynamic effects of TTFields are most likely too weak to disrupt normal microtubule electrophysiological activities significantly. Consequently, we posit that the observed cytoskeleton destruction in mitosis is more likely attributable to non-mechanical mechanisms.

The blood-brain barrier (BBB) limits the efficacy of treatments for malignant brain tumors, necessitating innovative approaches to breach the barrier. This study introduces burst sine wave electroporation (B-SWE) as a strategic modality for controlled BBB disruption without extensive tissue ablation and compares it against conventional pulsed square wave electroporation-based technologies such as high-frequency irreversible electroporation (H-FIRE). Using an in vivo rodent model, B-SWE and H-FIRE effects on BBB disruption, tissue ablation, and neuromuscular contractions are compared. Equivalent waveforms were designed for direct comparison between the two pulsing schemes, revealing that B-SWE induces larger BBB disruption volumes while minimizing tissue ablation. While B-SWE exhibited heightened neuromuscular contractions when compared to equivalent H-FIRE waveforms, an additional low-dose B-SWE group demonstrated that a reduced potential can achieve similar levels of BBB disruption while minimizing neuromuscular contractions. Repair kinetics indicated faster closure post B-SWE-induced BBB disruption when compared to equivalent H-FIRE protocols, emphasizing B-SWE's transient and controllable nature. Additionally, finite element modeling illustrated the potential for extensive BBB disruption while reducing ablation using B-SWE. B-SWE presents a promising avenue for tailored BBB disruption with minimal tissue ablation, offering a nuanced approach for glioblastoma treatment and beyond.

Silk fibroin (SF), which is extensively utilized in tissue engineering and vascular grafts for enhancing vascular regeneration, has not been thoroughly investigated for its epigenetic effects on endothelial cells (EC). This study employed RNA sequencing analysis to evaluate the activation of histone modification regulatory genes in EC treated with SF. Subsequent investigations revealed elevated H3K9me3 levels in SF-treated EC, as evidenced by immunofluorescence and western blot analysis. The study utilized H2B-eGFP endothelial cells to demonstrate that SF treatment results in the accumulation of H2B-marked chromatin in the nuclear inner cavities of EC. Inhibition of H3K9me3 levels by a histone deacetylase inhibitor TSA decreased cell proliferation. Furthermore, the activation of the MAPK signaling pathway using chromium picolinate decreased the proliferative activity and H3K9me3 level in SF-treated EC. SF also appeared to enhance cell growth and proliferation by modulating the H3K9me3 level and reorganizing chromatin, particularly after oxidative stress induced by H₂O₂ treatment. In summary, these findings indicate that SF promotes EC proliferation by increasing the H3K9me3 level even under stress conditions.

Crowding effects significantly influence the phase behavior and the structural and dynamic properties of the concentrated protein mixtures present in the cytoplasm of cells or in the blood serum. This poses enormous difficulties for our theoretical understanding and our ability to predict the behavior of these systems. While the use of course grained colloid-inspired models allows us to reproduce the key physical solution properties of concentrated monodisperse solutions of individual proteins, we lack corresponding theories for complex polydisperse mixtures. Here, we test the applicability of simple mixing rules in order to predict solution properties of protein mixtures. We use binary mixtures of the well-characterized bovine eye lens proteins α and γ_B crystallin as model systems. Combining microrheology with static and dynamic scattering techniques and observations of the phase diagram for liquid-liquid phase separation, we show that reasonably accurate descriptions are possible for macroscopic and mesoscopic signatures, while information on the length scale of the individual protein size requires more information on cross-component interaction.

The realm of implantable bioelectronics represents a frontier in medical science, merging technology, biology, and medicine to innovate treatments that enhance, restore, or monitor physiological functions. This field has yielded devices like cochlear implants, cardiac pacemakers, deep brain stimulators, and vagus nerve stimulators, each designed to address a specific health condition, ranging from sensorineural hearing loss to chronic pain, neurological disorders, and heart rhythm irregularities. Such devices underscore the potential of bioelectronics to significantly improve patient outcomes and quality of life. Recent technological breakthroughs in materials science, nanotechnology, and microfabrication have enabled the development of more sophisticated, smaller, and biocompatible bioelectronic devices. However, the field also encounters challenges, particularly in extending the capabilities of devices such as retinal prostheses, which aim to restore vision but currently offer limited visual acuity. Research in implantable bioelectronics is highly timely, driven by an aging global population with a growing prevalence of chronic diseases that could benefit from these technologies. The convergence of societal health needs, advancing technological capabilities, and a supportive ecosystem for innovation marks this era as pivotal for bioelectronic research.

Cardiovascular medical devices undergo a large number of pre- and post-market tests before their approval for clinical practice use. Sophisticated cardiovascular simulators can significantly expedite the evaluation process by providing a safe and controlled environment and representing clinically relevant case scenarios. The complex nature of the cardiovascular system affected by severe pathologies and the inherently intricate patient-device interaction creates a need for high-fidelity test benches able to reproduce intra- and inter-patient variability of disease states. Therefore, we propose an innovative cardiovascular simulator that combines in silico and in vitro modeling techniques with a soft robotic left ventricle. The simulator leverages patient-specific and echogenic soft robotic phantoms used to recreate the intracardiac pressure and volume waveforms, combined with an in silico lumped parameter model of the remaining cardiovascular system. Three different patient-specific profiles were recreated, to assess the capability of the simulator to represent a variety of working conditions and mechanical properties of the left ventricle. The simulator is shown to provide a realistic physiological and anatomical representation thanks to the use of soft robotics combined with in silico modeling. This tool proves valuable for optimizing and validating medical devices and delineating specific indications and boundary conditions.

Ascertaining the collective viability of cells in different cell culture conditions has typically relied on averaging colorimetric indicators and is often reported out in simple binary readouts. Recent research has combined viability assessment techniques with image-based deep-learning models to automate the characterization of cellular properties. However, further development of viability measurements to assess the continuity of possible cellular states and responses to perturbation across cell culture conditions is needed. In this work, we demonstrate an image processing algorithm for quantifying features associated with cellular viability in 3D cultures without the need for assay-based indicators. We show that our algorithm performs similarly to a pair of human experts in whole-well images over a range of days and culture matrix compositions. To demonstrate potential utility, we perform a longitudinal study investigating the impact of a known therapeutic on pancreatic cancer spheroids. Using images taken with a high content imaging system, the algorithm successfully tracks viability at the individual spheroid and whole-well level. The method we propose reduces analysis time by 97% in comparison with the experts. Because the method is independent of the microscope or imaging system used, this approach lays the foundation for accelerating progress in and for improving the robustness and reproducibility of 3D culture analysis across biological and clinical research.

[This corrects the article DOI: 10.1063/5.0147181.].

Perfusable microvascular networks offer promising three-dimensional in vitro models to study normal and compromised vascular tissues as well as phenomena such as cancer cell metastasis. Engineering of these microvascular networks generally involves the use of endothelial cells stabilized by fibroblasts to generate robust and stable vasculature. However, fibroblasts are highly heterogenous and may contribute variably to the microvascular structure. Here, we study the effect of normal and cancer-associated lung fibroblasts on the formation and function of perfusable microvascular networks. We examine the influence of cancer-associated fibroblasts on microvascular networks when cultured in direct (juxtacrine) and indirect (paracrine) contacts with endothelial cells, discovering a generative inhibition of microvasculature in juxtacrine co-cultures and a functional inhibition in paracrine co-cultures. Furthermore, we probed the secreted factors differential between cancer-associated fibroblasts and normal human lung fibroblasts, identifying several cytokines putatively influencing the resulting microvasculature morphology and functionality. These findings suggest the potential contribution of cancer-associated fibroblasts in aberrant microvasculature associated with tumors and the plausible application of such in vitro platforms in identifying new therapeutic targets and/or agents that can prevent formation of aberrant vascular structures.