Long noncoding RNA MALAT1 is dynamically regulated in leader cells during collective cancer invasion.

Cancer cells collectively invade using a leader-follower organization, but the regulation of leader cells during this dynamic process is poorly understood. Using a dual double-stranded locked nucleic acid (LNA) nanobiosensor that tracks long noncoding RNA (lncRNA) dynamics in live single cells, we monitored the spatiotemporal distribution of lncRNA during collective cancer invasion. We show that the lncRNA MALAT1 (metastasis-associated lung adenocarcinoma transcript 1) is dynamically regulated in the invading fronts of cancer cells and patient-derived spheroids. MALAT1 transcripts exhibit distinct abundance, diffusivity, and distribution between leader and follower cells. MALAT1 expression increases when a cancer cell becomes a leader and decreases when the collective migration process stops. Transient knockdown of MALAT1 prevents the formation of leader cells and abolishes the invasion of cancer cells. Taken together, our single-cell analysis suggests that MALAT1 is dynamically regulated in leader cells during collective cancer invasion.

Rapid Microbial Profiling through Multimodal Biosensors for Transversal Analysis.

The intricate interactions between host and microbial communities hold significant implications for biology and medicine. However, traditional microbial profiling methods face limitations in processing time, measurement of absolute abundance, detection of low biomass, discrimination between live and dead cells, and functional analysis. This study introduces a rapid multimodal microbial characterization platform, Multimodal Biosensors for Transversal Analysis (MBioTA), for capturing the taxonomy, viability, and functional genes of the microbiota. The platform incorporates single cell biosensors, scalable microwell arrays, and automated image processing for rapid transversal analysis in as few as 2 h. The multimodal biosensors simultaneously characterize the taxon, viability, and functional gene expression of individual cells. By automating the image processing workflow, the single cell analysis techniques enable the quantification of bacteria with sensitivity down to 0.0075%, showcasing its capability in detecting low biomass samples. We illustrate the applicability of the MBioTA platform through the transversal analysis of the gut microbiota composition, viability, and functionality in a familial Alzheimer's disease mouse model. The effectiveness, rapid turnaround, and scalability of the MBioTA platform will facilitate its application from basic research to clinical diagnostics, potentially revolutionizing our understanding and management of diseases associated with microbe-host interactions.

Transient nuclear deformation primes epigenetic state and promotes cell reprogramming.

Cell reprogramming has wide applications in tissue regeneration, disease modelling and personalized medicine. In addition to biochemical cues, mechanical forces also contribute to the modulation of the epigenetic state and a variety of cell functions through distinct mechanisms that are not fully understood. Here we show that millisecond deformation of the cell nucleus caused by confinement into microfluidic channels results in wrinkling and transient disassembly of the nuclear lamina, local detachment of lamina-associated domains in chromatin and a decrease of histone methylation (histone H3 lysine 9 trimethylation) and DNA methylation. These global changes in chromatin at the early stage of cell reprogramming boost the conversion of fibroblasts into neurons and can be partially reproduced by inhibition of histone H3 lysine 9 and DNA methylation. This mechanopriming approach also triggers macrophage reprogramming into neurons and fibroblast conversion into induced pluripotent stem cells, being thus a promising mechanically based epigenetic state modulation method for cell engineering.

Optimizing locked nucleic acid modification in double-stranded biosensors for live single cell analysis.

Double-stranded (ds) biosensors are homogeneous oligonucleotide probes for detection of nucleic acid sequences in biochemical assays and live cell imaging. Locked nucleic acid (LNA) modification can be incorporated in the biosensors to enhance the binding affinity, specificity, and resistance to nuclease degradation. However, LNA monomers in the quencher sequence can also prevent the target-fluorophore probe binding, which reduces the signal of the dsLNA biosensor. This study investigates the influence of LNA modification on dsLNA biosensors by altering the position and amount of LNA monomers present in the quencher sequence. We characterize the fluorophore-quencher interaction, target detection, and specificity of the biosensor in free solution and evaluate the performance of the dsLNA biosensor in 2D monolayers and 3D spheroids. The data indicate that a large amount of LNA monomers in the quencher sequence can enhance the specificity of the biosensor, but prevents effective target binding. Together, our results provide guidelines for improving the performance of dsLNA biosensors in nucleic acid detection and gene expression analysis in live cells.

Adaptable microfluidic system for single-cell pathogen classification and antimicrobial susceptibility testing.

Infectious diseases caused by bacterial pathogens remain one of the most common causes of morbidity and mortality worldwide. Rapid microbiological analysis is required for prompt treatment of bacterial infections and to facilitate antibiotic stewardship. This study reports an adaptable microfluidic system for rapid pathogen classification and antimicrobial susceptibility testing (AST) at the single-cell level. By incorporating tunable microfluidic valves along with real-time optical detection, bacteria can be trapped and classified according to their physical shape and size for pathogen classification. By monitoring their growth in the presence of antibiotics at the single-cell level, antimicrobial susceptibility of the bacteria can be determined in as little as 30 minutes compared with days required for standard procedures. The microfluidic system is able to detect bacterial pathogens in urine, blood cultures, and whole blood and can analyze polymicrobial samples. We pilot a study of 25 clinical urine samples to demonstrate the clinical applicability of the microfluidic system. The platform demonstrated a sensitivity of 100% and specificity of 83.33% for pathogen classification and achieved 100% concordance for AST.

Nonlinear Ride Height Control of Active Air Suspension System with Output Constraints and Time-Varying Disturbances.

This paper addresses the problem of nonlinear height tracking control of an automobile active air suspension with the output state constraints and time-varying disturbances. The proposed control strategy guarantees that the ride height stays within a predefined range, and converges closely to an arbitrarily small neighborhood of the desired height, ensuring uniform ultimate boundedness. The designed nonlinear observer is able to compensate for the time-varying disturbances caused by external random road excitation and perturbations, achieving robust performance. Simulation results obtained from the co-simulation (AMESim-Matlab/Simulink) are given and analyzed, demonstrating the efficiency of the proposed control methodology.

Three-Dimensional Microtumors for Probing Heterogeneity of Invasive Bladder Cancer.

Bladder cancer is an increasingly common malignancy, and muscle invasive bladder cancer is associated with particularly high rates of morbidity and mortality. The morphologic and molecular diversity of bladder cancer poses significant challenges in elucidating the invasion mechanisms responsible for disease progression. Furthermore, conventional invasion assays do not provide a physiological context for studying bladder cancer invasion within 3D microenvironments and have limited ability to capture the contribution of cellular phenotypic heterogeneity to disease progression. Here, we describe the development of a 3D microtumor invasion model suitable for the analysis of cellular phenotypic heterogeneity in cell lines and primary tumor cells from bladder cancer patients. This model incorporates a self-assembly approach for recapitulating features of bladder cancer invasion in 3D microenvironments and probing the invasive cell subpopulations. The gene expression profiles of invading microtumors were analyzed by incorporating a gold nanorod-locked nucleic acid biosensor. The incorporation of the single cell biosensor and transient gene knockdown into the system revealed the formation of invasive leader cells with upregulated Delta-like ligand 4 (DLL4) expression as well as the role of NOTCH1-DLL4 signaling in collective bladder cancer invasion. The involvement of DLL4 expressing cells in bladder cancer invasion was also observed in patient samples obtained from transurethral resection. Collectively, our study demonstrates a 3D microtumor invasion model for investigating intracellular heterogeneity of bladder cancer invasion and analyzing patient derived samples toward personalized medicine applications.

Automatic distinction between COVID-19 and common pneumonia using multi-scale convolutional neural network on chest CT scans.

The COVID-19 pneumonia is a global threat since it emerged in early December 2019. Driven by the desire to develop a computer-aided system for the rapid diagnosis of COVID-19 to assist radiologists and clinicians to combat with this pandemic, we retrospectively collected 206 patients with positive reverse-transcription polymerase chain reaction (RT-PCR) for COVID-19 and their 416 chest computed tomography (CT) scans with abnormal findings from two hospitals, 412 non-COVID-19 pneumonia and their 412 chest CT scans with clear sign of pneumonia are also retrospectively selected from participating hospitals. Based on these CT scans, we design an artificial intelligence (AI) system that uses a multi-scale convolutional neural network (MSCNN) and evaluate its performance at both slice level and scan level. Experimental results show that the proposed AI has promising diagnostic performance in the detection of COVID-19 and differentiating it from other common pneumonia under limited number of training data, which has great potential to assist radiologists and physicians in performing a quick diagnosis and mitigate the heavy workload of them especially when the health system is overloaded. The data is publicly available for further research at https://data.mendeley.com/datasets/3y55vgckg6/1https://data.mendeley.com/datasets/3y55vgckg6/1.

Increased Cardiac Arrhythmogenesis Associated With Gap Junction Remodeling With Upregulation of RNA-Binding Protein FXR1.

BACKGROUND: Gap junction remodeling is well established as a consistent feature of human heart disease involving spontaneous ventricular arrhythmia. The mechanisms responsible for gap junction remodeling that include alterations in the distribution of, and protein expression within, gap junctions are still debated. Studies reveal that multiple transcriptional and posttranscriptional regulatory pathways are triggered in response to cardiac disease, such as those involving RNA-binding proteins. The expression levels of FXR1 (fragile X mental retardation autosomal homolog 1), an RNA-binding protein, are critical to maintain proper cardiac muscle function; however, the connection between FXR1 and disease is not clear. METHODS: To identify the mechanisms regulating gap junction remodeling in cardiac disease, we sought to identify the functional properties of FXR1 expression, direct targets of FXR1 in human left ventricle dilated cardiomyopathy (DCM) biopsy samples and mouse models of DCM through BioID proximity assay and RNA immunoprecipitation, how FXR1 regulates its targets through RNA stability and luciferase assays, and functional consequences of altering the levels of this important RNA-binding protein through the analysis of cardiac-specific FXR1 knockout mice and mice injected with 3xMyc-FXR1 adeno-associated virus. RESULTS: FXR1 expression is significantly increased in tissue samples from human and mouse models of DCM via Western blot analysis. FXR1 associates with intercalated discs, and integral gap junction proteins Cx43 (connexin 43), Cx45 (connexin 45), and ZO-1 (zonula occludens-1) were identified as novel mRNA targets of FXR1 by using a BioID proximity assay and RNA immunoprecipitation. Our findings show that FXR1 is a multifunctional protein involved in translational regulation and stabilization of its mRNA targets in heart muscle. In addition, introduction of 3xMyc-FXR1 via adeno-associated virus into mice leads to the redistribution of gap junctions and promotes ventricular tachycardia, showing the functional significance of FXR1 upregulation observed in DCM. CONCLUSIONS: In DCM, increased FXR1 expression appears to play an important role in disease progression by regulating gap junction remodeling. Together this study provides a novel function of FXR1, namely, that it directly regulates major gap junction components, contributing to proper cell-cell communication in the heart.

DNA Transformer for Visualizing Endogenous RNA Dynamics in Live Cells.

The functions of RNA are tightly regulated via diverse intracellular mechanisms. However, probing the complex dynamics of endogenous RNA in live cells is a challenging task. In the present study, a DNA transformer is designed for visualizing the abundance, distribution, and mobility of endogenous mRNAs in live human cells. The transformable tetrahedral DNA (T-TED) probe has a flexible hinge structure and is programmed to conform into a 3D tetrahedron upon binding with the target mRNA. By incorporating Förster resonance energy transfer (FRET) imaging, super-resolution localization, and single particle tracking, the T-TED biosensor is applied for investigating the dynamics of Delta-like ligand 4 (Dll4) mRNA, which encodes a transmembrane protein, in human pulmonary microvascular endothelial cells. The data reveal unprecedented subpopulations of Dll4 mRNA with distinct mobility organized spatially in association with the endoplasmic reticulum and microtubule networks. The ability to monitor the dynamics of endogenous RNA in live human cells will provide a useful tool for studying the functions and regulation of RNA.

A Multiwell Microfluidic Device for Analyzing and Screening Nonhormonal Contraceptive Agents.

Birth control and family planning play pivotal roles in the economic growth and reduction of maternal, infant, and child mortality. Current contraceptives, such as hormonal agents and intrauterine devices, target only a small subset of reproductive processes and can have serious side effects on the health of women. To develop novel contraceptive agents, a scalable microfluidic device is established for analyzing and screening the effects of potential contraceptive agents on the maturation of the cumulus-oocyte complex. The microfluidic device performs on-chip incubation for studying oocyte maturation and cumulus expansion and isolates the microwells by oil-water interfaces to avoid crosstalk between the wells. A filter membrane is incorporated in the device to simplify incubation, medium exchange, washing, and fluorescence staining of oocytes. Cumulus expansion can be monitored directly in the device and oocyte maturation can be examined after enzymatic removal of cumulus cells and on-chip fluorescence staining. The performance of the device is evaluated by studying the influence of three drugs known to block oocyte maturation and/or cumulus expansion.

Optimizing peptide nucleic acid probes for hybridization-based detection and identification of bacterial pathogens.

Point-of-care (POC) diagnostics for infectious diseases have the potential to improve patient care and antibiotic stewardship. Nucleic acid hybridization is at the core of many amplification-free molecular diagnostics and detection probe configuration is key to diagnostic performance. Modified nucleic acids such as peptide nucleic acid (PNA) offer advantages compared to conventional DNA probes allowing for faster hybridization, better stability and minimal sample preparation for direct detection of pathogens. Probes with tethered fluorophore and quencher allow for solution-based assays and eliminate the need for washing steps thereby facilitating integration into microfluidic devices. Here, we compared the sensitivity and specificity of double stranded PNA probes (dsPNA) and PNA molecular beacons targeting E. coli and P. aeruginosa for direct detection of bacterial pathogens. In bulk fluid assays, the dsPNAs had an overall higher fluorescent signal and better sensitivity and specificity than the PNA beacons for pathogen detection. We further designed and tested an expanded panel of dsPNA probes for detection of a wide variety of pathogenic bacteria including probes for universal detection of eubacteria, Enterobacteriaceae family, and P. mirablis. To confirm that the advantage translated to other assay types we compared the PNA beacon and dsPNA in a prototype droplet microfluidic device. Beyond the bulk fluid assay and droplet devices, use of dsPNA probes may be advantageous in a wide variety of assays that employ homogenous nucleic acid hybridization.

Nanotube assisted microwave electroporation for single cell pathogen identification and antimicrobial susceptibility testing.

A nanotube assisted microwave electroporation (NAME) technique is demonstrated for delivering molecular biosensors into viable bacteria for multiplex single cell pathogen identification to advance rapid diagnostics in clinical microbiology. Due to the small volume of a bacterial cell (~femtoliter), the intracellular concentration of the target molecule is high, which results in a strong signal for single cell detection without amplification. The NAME procedure can be completed in as little as 30 minutes and can achieve over 90% transformation efficiency. We demonstrate the feasibility of NAME for identifying clinical isolates of bloodborne and uropathogenic pathogens and detecting bacterial pathogens directly from patient's samples. In conjunction with a microfluidic single cell trapping technique, NAME allows single cell pathogen identification and antimicrobial susceptibility testing concurrently. Using this approach, the time for microbiological analysis reduces from days to hours, which will have a significant impact on the clinical management of bacterial infections.

Low-level arsenic causes proteotoxic stress and not oxidative stress.

Prolonged exposure to arsenic has been shown to increase the risk of developing a number of diseases, including cancer and type II diabetes. Arsenic is present throughout the environment in its inorganic forms, and the level of exposure varies greatly by geographical location. The current recommended maximum level of arsenic exposure by the EPA is 10µg/L, but levels>50-1000µg/L have been detected in some parts of Asia, the Middle East, and the Southwestern United States. One of the most important steps in developing treatment options for arsenic-linked pathologies is to understand the cellular pathways affected by low levels of arsenic. Here, we show that acute exposure to non-lethal, low-level arsenite, an environmentally relevant arsenical, inhibits the autophagy pathway. Furthermore, arsenite-induced autophagy inhibition initiates a transient, but moderate ER stress response. Significantly, low-level arsenite exposure does not exhibit an increase in oxidative stress. These findings indicate that compromised autophagy, and not enhanced oxidative stress occurs early during arsenite exposure, and that restoring the autophagy pathway and proper proteostasis could be a viable option for treating arsenic-linked diseases. As such, our study challenges the existing paradigm that oxidative stress is the main underlying cause of pathologies associated with environmental arsenic exposure.

Knockout of Lmod2 results in shorter thin filaments followed by dilated cardiomyopathy and juvenile lethality.

Leiomodin 2 (Lmod2) is an actin-binding protein that has been implicated in the regulation of striated muscle thin filament assembly; its physiological function has yet to be studied. We found that knockout of Lmod2 in mice results in abnormally short thin filaments in the heart. We also discovered that Lmod2 functions to elongate thin filaments by promoting actin assembly and dynamics at thin filament pointed ends. Lmod2-KO mice die as juveniles with hearts displaying contractile dysfunction and ventricular chamber enlargement consistent with dilated cardiomyopathy. Lmod2-null cardiomyocytes produce less contractile force than wild type when plated on micropillar arrays. Introduction of GFP-Lmod2 via adeno-associated viral transduction elongates thin filaments and rescues structural and functional defects observed in Lmod2-KO mice, extending their lifespan to adulthood. Thus, to our knowledge, Lmod2 is the first identified mammalian protein that functions to elongate actin filaments in the heart; it is essential for cardiac thin filaments to reach a mature length and is required for efficient contractile force and proper heart function during development.

Cellular Architecture Regulates Collective Calcium Signaling and Cell Contractility.

A key feature of multicellular systems is the ability of cells to function collectively in response to external stimuli. However, the mechanisms of intercellular cell signaling and their functional implications in diverse vascular structures are poorly understood. Using a combination of computational modeling and plasma lithography micropatterning, we investigate the roles of structural arrangement of endothelial cells in collective calcium signaling and cell contractility. Under histamine stimulation, endothelial cells in self-assembled and microengineered networks, but not individual cells and monolayers, exhibit calcium oscillations. Micropatterning, pharmacological inhibition, and computational modeling reveal that the calcium oscillation depends on the number of neighboring cells coupled via gap junctional intercellular communication, providing a mechanistic basis of the architecture-dependent calcium signaling. Furthermore, the calcium oscillation attenuates the histamine-induced cytoskeletal reorganization and cell contraction, resulting in differential cell responses in an architecture-dependent manner. Taken together, our results suggest that endothelial cells can sense and respond to chemical stimuli according to the vascular architecture via collective calcium signaling.

Probing 3D Collective Cancer Invasion Using Double-Stranded Locked Nucleic Acid Biosensors.

Cancer is a leading cause of death worldwide and metastases are responsible for over 90% of human cancer deaths. There is an urgent need to develop novel therapeutics for suppressing cancer invasion, the initial step of metastasis. Nevertheless, the regulation of cancer invasion is poorly understood due to a paucity of tools for monitoring the invasion process in 3D microenvironments. Here, we report a double-stranded locked nucleic acid (dsLNA) biosensor for investigating 3D collective cancer invasion. By incorporating multiphoton microscopy and the dsLNA biosensor, we perform dynamic single cell gene expression analysis while simultaneously characterizing the biomechanical interaction between the invading sprouts and the extracellular matrix. Gene profiling of invasive leader cells and detached cells suggest distinctive signaling mechanisms involved in collective and individual invasion in the 3D microenvironment. Our results underscore the involvement of Notch signaling in 3D collective cancer invasion, which warrants further investigation toward antimetastasis therapy in the future.

Long-range electrothermal fluid motion in microfluidic systems.

AC electrothermal flow (ACEF) is the fluid motion created as a result of Joule heating induced temperature gradients. ACEF is capable of performing major microfluidic operations, such as pumping, mixing, concentration, separation and assay enhancement, and is effective in biological samples with a wide range of electrical conductivity. Here, we report long-range fluid motion induced by ACEF, which creates centimeter-scale vortices. The long-range fluid motion displays a strong voltage dependence and is suppressed in microchannels with a characteristic length below ~300 µm. An extended computational model of ACEF, which considers the effects of the density gradient and temperature-dependent parameters, is developed and compared experimentally by particle image velocimetry. The model captures the essence of ACEF in a wide range of channel dimensions and operating conditions. The combined experimental and computational study reveals the essential roles of buoyancy, temperature rise, and associated changes in material properties in the formation of the long-range fluid motion. Our results provide critical information for the design and modeling of ACEF based microfluidic systems toward various bioanalytical applications.

Multi-Objective Sliding Mode Control on Vehicle Cornering Stability with Variable Gear Ratio Actuator-Based Active Front Steering Systems.

Active front steering (AFS) is an emerging technology to improve the vehicle cornering stability by introducing an additional small steering angle to the driver's input. This paper proposes an AFS system with a variable gear ratio steering (VGRS) actuator which is controlled by using the sliding mode control (SMC) strategy to improve the cornering stability of vehicles. In the design of an AFS system, different sensors are considered to measure the vehicle state, and the mechanism of the AFS system is also modelled in detail. Moreover, in order to improve the cornering stability of vehicles, two dependent objectives, namely sideslip angle and yaw rate, are considered together in the design of SMC strategy. By evaluating the cornering performance, Sine with Dwell and accident avoidance tests are conducted, and the simulation results indicate that the proposed SMC strategy is capable of improving the cornering stability of vehicles in practice.

Simultaneous-Fault Diagnosis of Gearboxes Using Probabilistic Committee Machine.

This study combines signal de-noising, feature extraction, two pairwise-coupled relevance vector machines (PCRVMs) and particle swarm optimization (PSO) for parameter optimization to form an intelligent diagnostic framework for gearbox fault detection. Firstly, the noises of sensor signals are de-noised by using the wavelet threshold method to lower the noise level. Then, the Hilbert-Huang transform (HHT) and energy pattern calculation are applied to extract the fault features from de-noised signals. After that, an eleven-dimension vector, which consists of the energies of nine intrinsic mode functions (IMFs), maximum value of HHT marginal spectrum and its corresponding frequency component, is obtained to represent the features of each gearbox fault. The two PCRVMs serve as two different fault detection committee members, and they are trained by using vibration and sound signals, respectively. The individual diagnostic result from each committee member is then combined by applying a new probabilistic ensemble method, which can improve the overall diagnostic accuracy and increase the number of detectable faults as compared to individual classifiers acting alone. The effectiveness of the proposed framework is experimentally verified by using test cases. The experimental results show the proposed framework is superior to existing single classifiers in terms of diagnostic accuracies for both single- and simultaneous-faults in the gearbox.