APL Bioengineering最新文献

Activation of fibroblasts is pivotal for wound healing; however, persistent activation leads to maladaptive processes and is a hallmark of fibrosis, where disease mechanisms are only partially understood. Human in vitro model systems complement in vivo animal models for both hypothesis testing and drug evaluation to improve the identification of therapeutics relevant to human disease. Despite advances, a challenge remains in understanding the dynamics of human fibroblast responses to complex microenvironment stimuli, motivating the need for more advanced tools to investigate fibrotic mechanisms. This work established approaches for assessing the temporal dynamics of these responses using genetically encoded fluorescent reporters of alpha smooth muscle actin expression, an indicator of fibroblast activation. Specifically, we created a toolset of human lung fibroblast reporter cell lines from different origins (male, female; healthy, idiopathic pulmonary fibrosis) and used three different versions of the reporter with the fluorescent protein modified to exhibit different temporal stabilities, providing temporal resolution of protein expression processes over a range of timescales. Using this toolset, we demonstrated that reporters provide insight into population shifts in response to both mechanical and biochemical cues that are not detectable by traditional end point assessments with differential responses based on cell origin. Furthermore, individual cells can also be tracked over time, with opportunities for comparison to complementary end point measurements. The establishment of this reporter toolset enables dynamic cell investigations that can be translated into more complex synthetic culture environments for elucidating disease mechanisms and evaluating therapeutics for lung fibrosis and other complex biological processes more broadly.

Previous lung-on-chip devices have facilitated significant advances in our understanding of lung biology and pathology. Here, we describe a novel lung-on-a-chip model in which human induced pluripotent stem cell-derived alveolar epithelial type II cells (iAT2s) form polarized duct-like lumens alongside engineered perfused vessels lined with human umbilical vein endothelium, all within a 3D, physiologically relevant microenvironment. Using this model, we investigated the morphologic and signaling consequences of the KRAS^G12D mutation, a commonly identified oncogene in human lung adenocarcinoma (LUAD). We show that expression of the mutant KRAS^G12D isoform in iAT2s leads to a hyperproliferative response and morphologic dysregulation in the epithelial monolayer. Interestingly, the mutant epithelia also drive an angiogenic response in the adjacent vasculature that is mediated by enhanced secretion of the pro-angiogenic factor soluble uPAR. These results demonstrate the functionality of a multi-cellular in vitro platform capable of modeling mutation-specific behavioral and signaling changes associated with lung adenocarcinoma.

Micropipette aspiration (MPA) is one of the gold standards for quantifying biological samples' mechanical properties, which are crucial from the cell membrane scale to the multicellular tissue. However, relying on the manipulation of individual home-made glass pipettes, MPA suffers from low throughput and no automation. Here, we introduce the sliding insert micropipette aspiration method, which permits parallelization and automation, thanks to the insertion of tubular pipettes, obtained by photolithography, within microfluidic channels. We show its application both at the lipid bilayer level, by probing vesicles to measure membrane bending and stretching moduli, and at the tissue level by quantifying the viscoelasticity of 3D cell aggregates. This approach opens the way to high-throughput, quantitative mechanical testing of many types of biological samples, from vesicles and individual cells to cell aggregates and explants, under dynamic physico-chemical stimuli.

Lung cancer, the treacherous malignancy affecting the respiratory system of a human body, has a devastating impact on the health and well-being of an individual. Due to the lack of automated and noninvasive diagnostic tools, healthcare professionals look forward toward biopsy as a gold standard for diagnosis. However, biopsy could be traumatizing and expensive process. Additionally, the limited availability of dataset and inaccuracy in diagnosis is a major drawback experienced by researchers. The objective of the proposed research is to develop an automated diagnostic tool for screening of lung cancer using optimized hyperparameters such that convolutional neural network (CNN) model generalizes well for universally obtained computerized tomography (CT) slices of lung pathologies. The aforementioned objective is achieved in the following ways: (i) Initially, a preprocessing methodology specific to lung CT scans is formulated to avoid the loss of information due to random image smoothing, and (ii) a sine cosine algorithm optimization algorithm (SCA) is integrated in the CNN model, to optimally select the tuning parameters of CNN. The error rate is used as an objective function, and the SCA algorithm tries to minimize. The proposed method successfully achieved an average classification accuracy of 99% in classification of lung scans in normal, benign, and malignant classes. Further, the generalization ability of the proposed model is tested on unseen dataset, thereby achieving promising results. The quantitative results prove the efficacy of the system to be used by radiologists in a clinical scenario.

Tumor vasculature plays a crucial role in tumor progression, affecting nutrition and oxygen transportation as well as the efficiency of drug delivery. While targeting pro-angiogenic growth factors has been a significant focus for treating tumor angiogenesis, recent studies indicate that metabolism also plays a role in regulating endothelial cell behavior. Like cancer cells, tumor endothelial cells undergo metabolic changes that regulate rearrangement for tip cell position during angiogenesis. Our previous studies have shown that altered mechanical properties of the collagen matrix regulate angiogenesis and can promote a tumor vasculature phenotype. Here, we examine the effect of collagen density on endothelial cell tip-stalk cell rearrangement and cellular energetics during angiogenic sprouting. We find that increased collagen density leads to an elevated energy state and an increased rate of tip-stalk cell switching, which is correlated with the energy state of the cells. Tip cells exhibit higher glucose uptake than stalk cells, and inhibition of glucose uptake revealed that invading sprouts rely on glucose to meet elevated energy requirements for invasion in dense matrices. This work helps to elucidate the complex interplay between the mechanical microenvironment and the endothelial cell metabolic status during angiogenesis, which could have important implications for developing new anti-cancer therapies.

The understanding of cancer has evolved significantly, with the tumor microenvironment (TME) now recognized as a critical factor influencing the onset and progression of the disease. This broader perspective challenges the traditional view that cancer is primarily caused by mutations, instead emphasizing the dynamic interaction between different cell types and physicochemical factors within the TME. Among these factors, cancer-associated fibroblasts (CAFs) command attention for their profound influence on tumor behavior and patient prognoses. Despite their recognized importance, the biophysical and mechanical interactions of CAFs within the TME remain elusive. This review examines the distinctive physical characteristics of CAFs, their morphological attributes, and mechanical interactions within the TME. We discuss the impact of mechanotransduction on CAF function and highlight how these cells communicate mechanically with neighboring cancer cells, thereby shaping the path of tumor development and progression. By concentrating on the biomechanical regulation of CAFs, this review aims to deepen our understanding of their role in the TME and to illuminate new biomechanical-based therapeutic strategies.

Senescent cell accumulation in the pulmonary niche is associated with heightened susceptibility to age-related disease, tissue alterations, and ultimately a decline in lung function. Our current knowledge of senescent cell-extracellular matrix (ECM) dynamics is limited, and our understanding of how senescent cells influence spatial ECM architecture changes over time is incomplete. Herein is the design of an in vitro model of senescence-associated extracellular matrix (SA-ECM) remodeling using a senescent lung fibroblast-derived matrix that captures the spatiotemporal dynamics of an evolving senescent ECM architecture. Multiphoton second-harmonic generation microscopy was utilized to examine the spatial and temporal dynamics of fibroblast SA-ECM remodeling, which revealed a biphasic process that established a disordered and heterogeneous architecture. Additionally, we observed that inhibition of transforming growth factor-β signaling during SA-ECM remodeling led to improved local collagen fiber organization. Finally, we examined patient samples diagnosed with pulmonary fibrosis to further tie our results of the in vitro model to clinical outcomes. Moreover, we observed that the senescence marker p16 is correlated with local collagen fiber disorder. By elucidating the temporal dynamics of SA-ECM remodeling, we provide further insight on the role of senescent cells and their contributions to pathological ECM remodeling.

The myotendinous junction (MTJ) is the interface connecting skeletal muscle and tendon tissues. This specialized region represents the bridge that facilitates the transmission of contractile forces from muscle to tendon, and ultimately the skeletal system for the creation of movement. MTJs are, therefore, subject to high stress concentrations, rendering them susceptible to severe, life-altering injuries. Despite the scarcity of knowledge obtained from MTJ formation during embryogenesis, several attempts have been made to engineer this complex interfacial tissue. These attempts, however, fail to achieve the level of maturity and mechanical complexity required for in vivo transplantation. This review summarizes the strategies taken to engineer the MTJ, with an emphasis on how transitioning from static to mechanically inducive dynamic cultures may assist in achieving myotendinous maturity.

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.