High Throughput Confined Migration Microfluidic Device for Drug Screening

AI-Powered Microfluidics: Shaping the Future of Phenotypic Drug Discovery

Phenotypic drug discovery (PDD), which involves harnessing biological systems directly to uncover effective drugs, has undergone a resurgence in recent years. The rapid advancement of artificial intelligence (AI) over the past few years presents numerous opportunities for augmenting phenotypic drug screening on microfluidic platforms, leveraging its predictive capabilities, data analysis, efficient data processing, etc. Microfluidics coupled with AI is poised to revolutionize the landscape of phenotypic drug discovery. By integrating advanced microfluidic platforms with AI algorithms, researchers can rapidly screen large libraries of compounds, identify novel drug candidates, and elucidate complex biological pathways with unprecedented speed and efficiency. This review provides an overview of recent advances and challenges in AI-based microfluidics and their applications in drug discovery. We discuss the synergistic combination of microfluidic systems for high-throughput screening and AI-driven analysis for phenotype characterization, drug-target interactions, and predictive modeling. In addition, we highlight the potential of AI-powered microfluidics to achieve an automated drug screening system. Overall, AI-powered microfluidics represents a promising approach to shaping the future of phenotypic drug discovery by enabling rapid, cost-effective, and accurate identification of therapeutically relevant compounds.

Addressing Cardiovascular Toxicity Risk of Electronic Nicotine Delivery Systems in the Twenty-First Century: "What Are the Tools Needed for the Job?" and "Do We Have Them?"

Cigarette smoking is positively and robustly associated with cardiovascular disease (CVD), including hypertension, atherosclerosis, cardiac arrhythmias, stroke, thromboembolism, myocardial infarctions, and heart failure. However, after more than a decade of ENDS presence in the U.S. marketplace, uncertainty persists regarding the long-term health consequences of ENDS use for CVD. New approach methods (NAMs) in the field of toxicology are being developed to enhance rapid prediction of human health hazards. Recent technical advances can now consider impact of biological factors such as sex and race/ethnicity, permitting application of NAMs findings to health equity and environmental justice issues. This has been the case for hazard assessments of drugs and environmental chemicals in areas such as cardiovascular, respiratory, and developmental toxicity. Despite these advances, a shortage of widely accepted methodologies to predict the impact of ENDS use on human health slows the application of regulatory oversight and the protection of public health. Minimizing the time between the emergence of risk (e.g., ENDS use) and the administration of well-founded regulatory policy requires thoughtful consideration of the currently available sources of data, their applicability to the prediction of health outcomes, and whether these available data streams are enough to support an actionable decision. This challenge forms the basis of this white paper on how best to reveal potential toxicities of ENDS use in the human cardiovascular system-a primary target of conventional tobacco smoking. We identify current approaches used to evaluate the impacts of tobacco on cardiovascular health, in particular emerging techniques that replace, reduce, and refine slower and more costly animal models with NAMs platforms that can be applied to tobacco regulatory science. The limitations of these emerging platforms are addressed, and systems biology approaches to close the knowledge gap between traditional models and NAMs are proposed. It is hoped that these suggestions and their adoption within the greater scientific community will result in fresh data streams that will support and enhance the scientific evaluation and subsequent decision-making of tobacco regulatory agencies worldwide.

Biointerfaces with ultrathin patterns for directional control of cell migration

In the context of wound healing and tissue regeneration, precise control of cell migration direction is deemed crucial. To address this challenge, polydimethylsiloxane (PDMS) platforms with patterned 10 nm thick TiOx in arrowhead shape were designed and fabricated. Remarkably, without tall sidewall constraints, MC3T3-E1 cells seeded on these platforms were constrained to migrate along the tips of the arrowheads, as the cells were guided by the asymmetrical arrowhead tips which provided large contact areas. To the best of our knowledge, this is the first study demonstrating the use of thin TiOx arrowhead pattern in combination with a cell-repellent PDMS surface to provide guided cell migration unidirectionally without tall sidewall constraints. Additionally, high-resolution fluorescence imaging revealed that the asymmetrical distribution of focal adhesions, triggered by the patterned TiOx arrowheads with arm lengths of 10, 20, and 35 μm, promoted cell adhesion and protrusion along the arrowhead tip direction, resulting in unidirectional cell migration. These findings have important implications for the design of biointerfaces with ultrathin patterns to precisely control cell migration. Furthermore, microelectrodes were integrated with the patterned TiOx arrowheads to enable dynamic monitoring of cell migration using impedance measurement. This microfluidic device integrated with thin layer of guiding pattern and microelectrodes allows simultaneous control of directional cell migration and characterization of the cell movement of individual MC3T3-E1 cells, offering great potential for the development of biosensors for single-cell monitoring.

Noninvasive Assessment of hiPSC Differentiation toward Cardiomyocytes Using Pretrained Convolutional Neural Networks and the Channel Pruning Algorithm

Human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes (hiPSC-CMs) offer versatile applications in tissue engineering and drug screening. To facilitate the monitoring of hiPSC cardiac differentiation, a noninvasive approach using convolutional neural networks (CNNs) was explored. HiPSCs were differentiated into cardiomyocytes and analyzed using the quantitative real-time polymerase chain reaction (qRT-PCR). The bright-field images of the cells at different time points were captured to create the dataset. Six pretrained models (AlexNet, GoogleNet, ResNet 18, ResNet 50, DenseNet 121, VGG 19-BN) were employed to identify different stages in differentiation. VGG 19-BN outperformed the other five CNNs and exhibited remarkable performance with 99.2% accuracy, recall, precision, and F1 score and 99.8% specificity. The pruning process was then applied to the optimal model, resulting in a significant reduction of model parameters while maintaining high accuracy. Finally, an automation application using the pruned VGG 19-BN model was developed, facilitating users in assessing the cell status during the myocardial differentiation of hiPSCs.

Microfluidic single-cell migration chip reveals insights into the impact of extracellular matrices on cell movement

Cell migration is a complex process that plays a crucial role in normal physiology and pathologies such as cancer, autoimmune diseases, and mental disorders. Conventional cell migration assays face limitations in tracking a large number of individual migrating cells. To address this challenge, we have developed a high-throughput microfluidic cell migration chip, which seamlessly integrates robotic liquid handling and computer vision to swiftly monitor the movement of 3200 individual cells, providing unparalleled single-cell resolution for discerning distinct behaviors of the fast-moving cell population. This study focuses on the ECM's role in regulating cellular migration, utilizing this cutting-edge microfluidic technology to investigate the impact of ten different ECMs on triple-negative breast cancer cell lines. We found that collagen IV, collagen III, and collagen I coatings were the top enhancers of cell movement. Combining these ECMs increased cell motility, but the effect was sub-additive. Furthermore, we examined 87 compounds and found that while some compounds inhibited migration on all substrates, significantly distinct effects on differently coated substrates were observed, underscoring the importance of considering ECM coating. We also utilized cells expressing a fluorescent actin reporter and observed distinct actin structures in ECM-interacting cells. ScRNA-Seq analysis revealed that ECM coatings induced EMT and enhanced cell migration. Finally, we identified genes that were particularly up-regulated by collagen IV and the selective inhibitors successfully blocked cell migration on collagen IV. Overall, the study provides insights into the impact of various ECMs on cell migration and dynamics of cell movement with implications for developing therapeutic strategies to combat diseases related to cell motility.

Recent Developments in Inertial and Centrifugal Microfluidic Systems along with the Involved Forces for Cancer Cell Separation: A Review

The treatment of cancers is a significant challenge in the healthcare context today. Spreading circulating tumor cells (CTCs) throughout the body will eventually lead to cancer metastasis and produce new tumors near the healthy tissues. Therefore, separating these invading cells and extracting cues from them is extremely important for determining the rate of cancer progression inside the body and for the development of individualized treatments, especially at the beginning of the metastasis process. The continuous and fast separation of CTCs has recently been achieved using numerous separation techniques, some of which involve multiple high-level operational protocols. Although a simple blood test can detect the presence of CTCs in the blood circulation system, the detection is still restricted due to the scarcity and heterogeneity of CTCs. The development of more reliable and effective techniques is thus highly desired. The technology of microfluidic devices is promising among many other bio-chemical and bio-physical technologies. This paper reviews recent developments in the two types of microfluidic devices, which are based on the size and/or density of cells, for separating cancer cells. The goal of this review is to identify knowledge or technology gaps and to suggest future works.

Porous Structural Microfluidic Device for Biomedical Diagnosis: A Review

Microfluidics has recently received more and more attention in applications such as biomedical, chemical and medicine. With the development of microelectronics technology as well as material science in recent years, microfluidic devices have made great progress. Porous structures as a discontinuous medium in which the special flow phenomena of fluids lead to their potential and special applications in microfluidics offer a unique way to develop completely new microfluidic chips. In this article, we firstly introduce the fabrication methods for porous structures of different materials. Then, the physical effects of microfluid flow in porous media and their related physical models are discussed. Finally, the state-of-the-art porous microfluidic chips and their applications in biomedicine are summarized, and we present the current problems and future directions in this field.

Lysyl hydroxylase LH1 promotes confined migration and metastasis of cancer cells by stabilizing Septin2 to enhance actin network

BACKGROUND

Excessive extracellular matrix deposition and increased stiffness are typical features of solid tumors such as hepatocellular carcinoma (HCC) and pancreatic ductal adenocarcinoma (PDAC). These conditions create confined spaces for tumor cell migration and metastasis. The regulatory mechanism of confined migration remains unclear.

METHODS

LC-MS was applied to determine the differentially expressed proteins between HCC tissues and corresponding adjacent tissue. Collective migration and single cell migration microfluidic devices with 6 μm-high confined channels were designed and fabricated to mimic the in vivo confined space. 3D invasion assay was created by Matrigel and Collagen I mixture treat to adherent cells. 3D spheroid formation under various stiffness environment was developed by different substitution percentage GelMA. Immunoprecipitation was performed to pull down the LH1-binding proteins, which were identified by LC-MS. Immunofluorescent staining, FRET, RT-PCR, Western blotting, FRAP, CCK-8, transwell cell migration, wound healing, orthotopic liver injection mouse model and in vivo imaging were used to evaluate the target expression and cellular phenotype.

RESULTS

Lysyl hydroxylase 1 (LH1) promoted the confined migration of cancer cells at both collective and single cell levels. In addition, LH1 enhanced cell invasion in a 3D biomimetic model and spheroid formation in stiffer environments. High LH1 expression correlated with poor prognosis of both HCC and PDAC patients, while it also promoted in vivo metastasis. Mechanistically, LH1 bound and stabilized Septin2 (SEPT2) to enhance actin polymerization, depending on the hydroxylase domain. Finally, the subpopulation with high expression of both LH1 and SEPT2 had the poorest prognosis.

CONCLUSIONS

LH1 promotes the confined migration and metastasis of cancer cells by stabilizing SEPT2 and thus facilitating actin polymerization.