A review of recent progress toward the efficient separation of circulating tumor cells via micro‐/nanostructured microfluidic chips

Engineering Innervated Musculoskeletal Tissues for Regenerative Orthopedics and Disease Modeling

Musculoskeletal (MSK) disorders significantly burden patients and society, resulting in high healthcare costs and productivity loss. These disorders are the leading cause of physical disability, and their prevalence is expected to increase as sedentary lifestyles become common and the global population of the elderly increases. Proper innervation is critical to maintaining MSK function, and nerve damage or dysfunction underlies various MSK disorders, underscoring the potential of restoring nerve function in MSK disorder treatment. However, most MSK tissue engineering strategies have overlooked the significance of innervation. This review first expounds upon innervation in the MSK system and its importance in maintaining MSK homeostasis and functions. This will be followed by strategies for engineering MSK tissues that induce post-implantation in situ innervation or are pre-innervated. Subsequently, research progress in modeling MSK disorders using innervated MSK organoids and organs-on-chips (OoCs) is analyzed. Finally, the future development of engineering innervated MSK tissues to treat MSK disorders and recapitulate disease mechanisms is discussed. This review provides valuable insights into the underlying principles, engineering methods, and applications of innervated MSK tissues, paving the way for the development of targeted, efficacious therapies for various MSK conditions.

Extracorporeal Blood Treatment Using Functional Magnetic Nanoclusters Mitigates Organ Dysfunction of Sepsis in Swine

Mitigating sepsis-induced severe organ dysfunction with magnetic nanoparticles has shown remarkable advances in extracorporeal blood treatment. Nevertheless, treating large septic animals remains challenging due to insufficient magnetic separation at rapid blood flow rates (>6 L h-1) and limited incubation time in an extracorporeal circuit. Herein, superparamagnetic nanoclusters (SPNCs) coated with red blood cell (RBC) membranes are developed, which promptly capture and magnetically separate a wide range of pathogens at high blood flow rates in a swine sepsis model. The SPNCs exhibited an ultranarrow size distribution of clustered iron oxide nanocrystals and exceptionally high saturation magnetization (≈ 90 emu g-1) close to that of bulk magnetite. It is also revealed that CD47 on the RBCs allows the RBC-SPNCs to remain at a consistent concentration in the blood by evading innate immunity. The uniform size distribution of the RBC-SPNCs greatly enhances their effectiveness in eradicating various pathogenic materials in extracorporeal blood. The use of RBC-SPNCs for extracorporeal treatment of swine infected with multidrug-resistant E. coli is validated and found that severe bacteremic sepsis-induced organ dysfunction is significantly mitigated after 12 h. The findings highlight the potential application of RBC-SPNCs for extracorporeal therapy of severe sepsis in large animal models and potentially humans.

Decoding Biomechanical Cues Based on DNA Sensors

Biological systems perceive and respond to mechanical forces, generating mechanical cues to regulate life processes. Analyzing biomechanical forces has profound significance for understanding biological functions. Therefore, a series of molecular mechanical techniques have been developed, mainly including single-molecule force spectroscopy, traction force microscopy, and molecular tension sensor systems, which provide indispensable tools for advancing the field of mechanobiology. DNA molecules with a programmable structure and well-defined mechanical characteristics have attached much attention to molecular tension sensors as sensing elements, and are designed for the study of biomechanical forces to present biomechanical information with high sensitivity and resolution. In this work, a comprehensive overview of molecular mechanical technology is presented, with a particular focus on molecular tension sensor systems, specifically those based on DNA. Finally, the future development and challenges of DNA-based molecular tension sensor systems are looked upon.

Irreversible Bonding of Polydimethylsiloxane-Lithium Niobate using Oxygen Plasma Modification for Surface Acoustic Wave based Microfluidic Application: Theory and Experiment

Acoustic microfluidic chips, fabricated by combining lithium niobate (LiNbO3) with polydimethylsiloxane (PDMS), practically find applications in biomedicine. However, high-strength direct bonding of LiNbO3 substrate with PDMS microchannel remains a challenge due to the large mismatching of thermal expansion coefficient at the interface and the lack of bonding theory. This paper elaborately reveals the bonding mechanisms of PDMS and LiNbO3, demonstrating an irreversible bonding method for PDMS-LiNbO3 heterostructures using oxygen plasma modification. An in-situ monitoring strategy by using resonant devices is proposed for oxygen plasma, including quartz crystal microbalance (QCM) covered with PDMS and surface acoustic wave (SAW) fabricated by LiNbO3. When oxygen plasma exposure occurs, surfaces are cleaned, oxygen ions are implanted, and hydroxyl groups (-OH) are formed. Upon interfaces bonding, the interface will form niobium-oxygen-silicon covalent bonds to realize an irreversible connection. A champion bonding strength is obtained of 1.1 MPa, and the PDMS-LiNbO3 acoustic microfluidic chip excels in leakage tests, withstanding pressures exceeding 60 psi, outperforming many previously reported devices. This work addresses the gap in PDMS-LiNbO3 bonding theory and advances its practical application in the acoustic microfluidic field.

Droplet Microfluidic Devices: Working Principles, Fabrication Methods, and Scale-Up Applications

Compared with the conventional emulsification method, droplets generated within microfluidic devices exhibit distinct advantages such as precise control of fluids, exceptional monodispersity, uniform morphology, flexible manipulation, and narrow size distribution. These inherent benefits, including intrinsic safety, excellent heat and mass transfer capabilities, and large surface-to-volume ratio, have led to the widespread applications of droplet-based microfluidics across diverse fields, encompassing chemical engineering, particle synthesis, biological detection, diagnostics, emulsion preparation, and pharmaceuticals. However, despite its promising potential for versatile applications, the practical utilization of this technology in commercial and industrial is extremely limited to the inherently low production rates achievable within a single microchannel. Over the past two decades, droplet-based microfluidics has evolved significantly, considerably transitioning from a proof-of-concept stage to industrialization. And now there is a growing trend towards translating academic research into commercial and industrial applications, primarily driven by the burgeoning demands of various fields. This paper comprehensively reviews recent advancements in droplet-based microfluidics, covering the fundamental working principles and the critical aspect of scale-up integration from working principles to scale-up integration. Based on the existing scale-up strategies, the paper also outlines the future research directions, identifies the potential opportunities, and addresses the typical unsolved challenges.

Recent Progress in Mass Spectrometry-Based Single-Cell Metabolic Analysis

Single-cell analysis enables the measurement of biomolecules at the level of individual cells, facilitating in-depth investigations into cellular heterogeneity and precise interpretation of the related biological mechanisms. Among these biomolecules, cellular metabolites exhibit remarkable sensitivity to environmental and biochemical changes, unveiling a hidden world underlying cellular heterogeneity and allowing for the determination of cell physiological states. However, the metabolic analysis of single cells is challenging due to the extremely low concentrations, substantial content variations, and rapid turnover rates of cellular metabolites. Mass spectrometry (MS), characterized by its high sensitivity, wide dynamic range, and excellent selectivity, is employed in single-cell metabolic analysis. This review focuses on recent advances and applications of MS-based single-cell metabolic analysis, encompassing three key steps of single-cell isolation, detection, and application. It is anticipated that MS will bring profound implications in biomedical practices, serving as advanced tools to depict the single-cell metabolic landscape.

Highly Multiplexed, Efficient, and Automated Single-Cell MicroRNA Sequencing with Digital Microfluidics

Single-cell microRNA (miRNA) sequencing has allowed for comprehensively studying the abundance and complex networks of miRNAs, which provides insights beyond single-cell heterogeneity into the dynamic regulation of cellular events. Current benchtop-based technologies for single-cell miRNA sequencing are low throughput, limited reaction efficiency, tedious manual operations, and high reagent costs. Here, a highly multiplexed, efficient, integrated, and automated sample preparation platform is introduced for single-cell miRNA sequencing based on digital microfluidics (DMF), named Hiper-seq. The platform integrates major steps and automates the iterative operations of miRNA sequencing library construction by digital control of addressable droplets on the DMF chip. Based on the design of hydrophilic micro-structures and the capability of handling droplets of DMF, multiple single cells can be selectively isolated and subject to sample processing in a highly parallel way, thus increasing the throughput and efficiency for single-cell miRNA measurement. The nanoliter reaction volume of this platform enables a much higher miRNA detection ability and lower reagent cost compared to benchtop methods. It is further applied Hiper-seq to explore miRNAs involved in the ossification of mouse skeletal stem cells after bone fracture and discovered unreported miRNAs that regulate bone repairing.

Next-Generation Preclinical Functional Testing Models in Cancer Precision Medicine: CTC-Derived Organoids

Basic and clinical cancer research requires tumor models that consistently recapitulate the characteristics of prima tumors. As ex vivo 3D cultures of patient tumor cells, patient-derived tumor organoids possess the biological properties of primary tumors and are therefore excellent preclinical models for cancer research. Patient-derived organoids can be established using primary tumor tissues, peripheral blood, pleural fluid, ascites, and other samples containing tumor cells. Circulating tumor cells acquired by non-invasive sampling feature dynamic circulation and high heterogeneity. Circulating tumor cell-derived organoids are prospective tools for the dynamic monitoring of tumor mutation evolution profiles because they reflect the heterogeneity of the original tumors to a certain extent. This review discusses the advantages and applications of patient-derived organoids. Meanwhile, this work highlights the biological functions of circulating tumor cells, the latest advancement in research of circulating tumor cell-derived organoids, and potential application and challenges of this technology.

Designed Nanomaterials-Assisted Proteomics and Metabolomics Analysis for In Vitro Diagnosis

In vitro diagnosis (IVD) is pivotal in modern medicine, enabling early disease detection and treatment optimization. Omics technologies, particularly proteomics and metabolomics, offer profound insights into IVD. Despite its significance, omics analyses for IVD face challenges, including low analyte concentrations and the complexity of biological environments. In addition, the direct omics analysis by mass spectrometry (MS) is often hampered by issues like large sample volume requirements and poor ionization efficiency. Through manipulating their size, surface charge, and functionalization, as well as the nanoparticle-fluid incubation conditions, nanomaterials have emerged as a promising solution to extract biomolecules and enhance the desorption/ionization efficiency in MS detection. This review delves into the last five years of nanomaterial applications in omics, focusing on their role in the enrichment, separation, and ionization analysis of proteins and metabolites for IVD. It aims to provide a comprehensive update on nanomaterial design and application in omics, highlighting their potential to revolutionize IVD.

High-Throughput 3D Imaging Flow Cytometry of Suspended Adherent 3D Cell Cultures

3D cell cultures are indispensable in recapitulating in vivo environments. Among the many 3D culture methods, culturing adherent cells on hydrogel beads to form spheroid-like structures is a powerful strategy for maintaining high cell viability and functions in the adherent states. However, high-throughput, scalable technologies for 3D imaging of individual cells cultured on the hydrogel scaffolds are lacking. This study reports the development of a high throughput, scalable 3D imaging flow cytometry platform for analyzing spheroid models. This platform is realized by integrating a single objective fluorescence light-sheet microscopy with a microfluidic device that combines hydrodynamic and acoustofluidic focusing techniques. This integration enabled unprecedentedly high-throughput and scalable optofluidic 3D imaging, processing 1310 spheroids consisting of 28 117 cells min-1 . The large dataset obtained enables precise quantification and comparison of the nuclear morphology of adhering and suspended cells, revealing that the adhering cells have smaller nuclei with less rounded surfaces. This platform's high throughput, robustness, and precision for analyzing the morphology of subcellular structures in 3D culture models hold promising potential for various biomedical analyses, including image-based phenotypic screening of drugs with spheroids or organoids.

Integrative Serum Metabolic Fingerprints Based Multi-Modal Platforms for Lung Adenocarcinoma Early Detection and Pulmonary Nodule Classification

Identification of novel non-invasive biomarkers is critical for the early diagnosis of lung adenocarcinoma (LUAD), especially for the accurate classification of pulmonary nodule. Here, a multiplexed assay is developed on an optimized nanoparticle-based laser desorption/ionization mass spectrometry platform for the sensitive and selective detection of serum metabolic fingerprints (SMFs). Integrative SMFs based multi-modal platforms are constructed for the early detection of LUAD and the classification of pulmonary nodule. The dual modal model, metabolic fingerprints with protein tumor marker neural network (MP-NN), integrating SMFs with protein tumor marker carcinoembryonic antigen (CEA) via deep learning, shows superior performance compared with the single modal model Met-NN (p < 0.001). Based on MP-NN, the tri modal model MPI-RF integrating SMFs, tumor marker CEA, and image features via random forest demonstrates significantly higher performance than the clinical models (Mayo Clinic and Veterans Affairs) and the image artificial intelligence in pulmonary nodule classification (p < 0.001). The developed platforms would be promising tools for LUAD screening and pulmonary nodule management, paving the conceptual and practical foundation for the clinical application of omics tools.