A Novel Electrokinetic-Based Technique for the Isolation of Circulating Tumor Cells.

The separation of rare cells from complex biofluids has attracted attention in biological research and clinical applications, especially for cancer detection and treatment. In particular, various technologies and methods have been developed for the isolation of circulating tumor cells (CTCs) in the blood. Among them, the induced-charge electrokinetic (ICEK) flow method has shown its high efficacy for cell manipulation where micro-vortices (MVs), generated as a result of induced charges on a polarizable surface, can effectively manipulate particles and cells in complex fluids. While the majority of MVs have been induced by AC electric fields, these vortices have also been observed under a DC electric field generated around a polarizable hurdle. In the present numerical work, the capability of MVs for the manipulation of CTCs and their entrapment in the DC electric field is investigated. First, the numerical results are verified against the available data in the literature. Then, various hurdle geometries are employed to find the most effective geometry for MV-based particle entrapment. The effects of electric field strength (EFS), wall zeta potential magnitude, and the particles' diameter on the trapping efficacy are further investigated. The results demonstrated that the MVs generated around only the rectangular hurdle are capable of trapping particles as large as the size of CTCs. An EFS of about 75 V/cm was shown to be effective for the entrapment of above 90% of CTCs in the MVs. In addition, an EFS of 85 V/cm demonstrated a capability for isolating particles larger than 8 µm from a suspension of particles/cells 1-25 µm in diameter, useful for the enrichment of cancer cells and potentially for the real-time and non-invasive monitoring of drug effectiveness on circulating cancer cells in blood circulation.

Nanoporous Carbon Immunosensor for Highly Accurate and Sensitive Clinical Detection of Glial Fibrillary Acidic Protein in Traumatic Brain Injury, Stroke, and Spinal Cord Injury.

Elevated glial fibrillary acidic protein (GFAP) in the blood serum is one of the promising bodily fluid markers for the diagnosis of central nervous system (CNS) injuries, including traumatic brain injury (TBI), stroke, and spinal cord injury (SCI). However, accurate and point-of-care (POC) quantification of GFAP in clinical blood samples has been challenging and yet to be clinically validated against gold-standard assays and outcome practices. This work engineered and characterized a novel nanoporous carbon screen-printed electrode with significantly increased surface area and conductivity, as well as preserved stability and anti-fouling properties. This nano-decorated electrode was immobilized with the target GFAP antibody to create an ultrasensitive GFAP immunosensor and quantify GFAP levels in spiked samples and the serum of CNS injury patients. The immunosensor presented a dynamic detection range of 100 fg/mL to 10 ng/mL, a limit of detection of 86.6 fg/mL, and a sensitivity of 20.3 Ω mL/pg mm2 for detecting GFAP in the serum. Its clinical utility was demonstrated by the consistent and selective quantification of GFAP comparable to the ultrasensitive single-molecule array technology in 107 serum samples collected from TBI, stroke, and SCI patients. Comparing the diagnostic and prognostic performance of the immunosensor with the existing clinical paradigms confirms the immunosensor's accuracy as a potential complement to the existing imaging diagnostic modalities and presents a potential for rapid, accurate, cost-effective, and near real-time POC diagnosis and prognosis of CNS injuries.

MicroSweat: A Wearable Microfluidic Patch for Noninvasive and Reliable Sweat Collection Enables Human Stress Monitoring.

Stress affects cognition, behavior, and physiology, leading to lasting physical and mental illness. The ability to detect and measure stress, however, is poor. Increased circulating cortisol during stress is mirrored by cortisol release from sweat glands, providing an opportunity to use it as an external biomarker for monitoring internal emotional state. Despite the attempts at using wearable sensors for monitoring sweat cortisol, there is a lack of reliable wearable sweat collection devices that preserve the concentration and integrity of sweat biomolecules corresponding to stress levels. Here, a flexible, self-powered, evaporation-free, bubble-free, surfactant-free, and scalable capillary microfluidic device, MicroSweat, is fabricated to reliably collect human sweat from different body locations. Cortisol levels are detected corresponding to severe stress ranging from 25 to 125 ng mL-1 averaged across multiple body regions and 100-1000 ng mL-1 from the axilla. A positive nonlinear correlation exists between cortisol concentration and stress levels quantified using the perceived stress scale (PSS). Moreover, owing to the sweat variation in response to environmental effects and physiological differences, the longitudinal and personalized profile of sweat cortisol is acquired, for the first time, for various body locations. The obtained sweat cortisol data is crucial for analyzing human stress in personalized and clinical healthcare sectors.

A Low-Cost Handheld Impedimetric Biosensing System for Rapid Diagnostics of SARS-CoV-2 Infections.

Current laboratory diagnostic approaches for virus detection give reliable results, but they require a lengthy procedure, trained personnel, and expensive equipment and reagents; hence, they are not a suitable choice for home monitoring purposes. This paper addresses this challenge by developing a portable impedimetric biosensing system for the identification of COVID-19 patients. This sensing system has two main parts: a throwaway two-working electrode (2-WE) strip and a novel read-out circuit, specifically designed for simultaneous signal acquisition from both working electrodes. Highly reliable electrochemical signal tracking from multiplex immunosensors provides a potential for flexible and portable multi-biomarker detection. The electrodes' surfaces were functionalized with SARS-CoV-2 Nucleocapsid Antibody enabling the selective detection of Nucleocapsid protein (N-protein) along with self-validation in the clinical nasopharyngeal swab specimens. The proposed programmable highly sensitive impedance read-out system allows for a wide dynamic detection range, which makes the sensor capable of detecting N-protein concentrations between 0.116 and 10,000 pg/mL. This lightweight and economical read-out arrangement is an ideal prospect for being mass-produced, especially during urgent pandemic situations. Also, such an impedimetric sensing platform has the potential to be redesigned for targeting not only other infectious diseases but also other critical disorders.

Self-assembly of highly ordered micro- and nanoparticle deposits.

The evaporation of particle-laden sessile droplets is associated with capillary-driven outward flow and leaves nonuniform coffee-ring-like particle patterns due to far-from-equilibrium effects. Traditionally, the surface energies of the drop and solid phases are tuned, or external forces are applied to suppress the coffee-ring; however, achieving a uniform and repeatable particle deposition is extremely challenging. Here, we report a simple, scalable, and noninvasive technique that yields uniform and exceptionally ordered particle deposits on a microscale surface area by placing the droplet on a near neutral-wet shadow mold attached to a hydrophilic substrate. The simplicity of the method, no external forces, and no tuning materials' physiochemical properties make the present generic approach an excellent candidate for a wide range of sensitive applications. We demonstrate the utility of this method for fabricating ordered mono- and multilayer patternable coatings, producing nanofilters with controlled pore size, and creating reproducible functionalized nanosensors.

A compact, low-cost, and binary sensing (BiSense) platform for noise-free and self-validated impedimetric detection of COVID-19 infected patients.

Electrochemical immuno-biosensors are one of the most promising approaches for accurate, rapid, and quantitative detection of protein biomarkers. The two-working electrode strip is employed for creating a self-supporting system, as a tool for self-validating the acquired results for added reliability. However, the realization of multiplex electrochemical point-of-care testing (ME-POCT) requires advancement in portable, rapid reading, easy-to-use, and low-cost multichannel potentiostat readers. The combined multiplex biosensor strips and multichannel readers allow for suppressing the possible complex matrix effect or ultra-sensitive detection of different protein biomarkers. Herein, a handheld binary-sensing (BiSense) bi-potentiostat was developed to perform electrochemical impedance spectroscopy (EIS)-based signal acquisition from a custom-designed dual-working-electrode immuno-biosensor. BiSense employs a commercially available microcontroller and out-of-shelf components, offering the cheapest yet accurate and reliable time-domain impedance analyzer. A specific electrical board design was developed and customized for impedance signal analysis of SARS-CoV-2 nucleocapsid (N)-protein biosensor in spiked samples and alpha variant clinical nasopharyngeal (NP) swab samples. BiSense showed limit-of-detection (LoD) down to 56 fg/mL for working electrode 1 (WE1) and 68 fg/mL for WE2 and reported with a dynamic detection range of 1 pg/mL to 10 ng/mL for detection of N-protein in spiked samples. The dual biosensing of N-protein in this work was used as a self-validation of the biosensor. The low-cost (∼USD$40) BiSense bi-potentiostat combined with the immuno-biosensors successfully detected COVID-19 infected patients in less than 10 min, with the BiSense reading period shorter than 1.5 min, demonstrating its potential for the realization of ME-POCTs for rapid and hand-held diagnosis of infections.

Autonomous electrochemical biosensing of glial fibrillary acidic protein for point-of-care detection of central nervous system injuries.

The integration of electrochemical biosensors into fluid handling units such as paper-based, centrifugal, and capillary microfluidic devices has been explored with the purpose of developing point-of-care platforms for quantitative detection of bodily fluid markers. However, the present fluidic device designs largely lack the capacity of full assay automation, needing manual loading of one or multiple reagents or requiring external devices for liquid manipulation. Such fluidic handing platforms also require universality for detecting various biomarkers. These platforms are also largely produced using materials unsuitable for scalable manufacturing and with a high production cost. The mechanism of fluid flow also often induces noise to the embedded biosensors which adversely impacts the accuracy of biosensing. This work addresses these challenges by presenting a reliable design of a fully automated and universal capillary-driven microfluidic platform that automates several steps of label-free electrochemical biosensing assays. These steps include sample aliquoting, controlled incubation, removal of non-specific bindings, reagent mixing and delivery to sensing electrodes, and electrochemical detection. The multilayer architecture of the microfluidic device is made of polymeric and adhesive materials commercially used for the fabrication of point-of-care devices. The design and geometry of different components of the device (e.g., sampling unit, mixer, resistances, delay valves, interconnecting components) were optimized using a combined experimental testing and numerical fluid flow modeling to reach high reproducibility and minimize the noise-induced to the biosensor. As a proof of concept, the performance of this on-chip immunosensing platform was demonstrated for rapid and autonomous detection of glial fibrillary acidic proteins (GFAP) in phosphate-buffered saline (PBS). The microfluidic immunosensing device exhibited a linear detection range of 10-1000 pg mL-1 for the detection of GFAP within 30 min, with a limit of detection (LoD) and sensitivity of 3 pg mL-1 and 39 mL pg-1 mm-2 in PBS, respectively. Owing to its simplicity, sample-to-result performance, universality for handing different biofluids, low cost, high reproducibility, compatibility with scalable production, and short analysis time, the proposed biosensing platform can be further adapted for the detection of other biomarkers in different clinical bodily fluids for rapid diagnostic and prognostic applications.

Bi-ECDAQ: An electrochemical dual-immuno-biosensor accompanied by a customized bi-potentiostat for clinical detection of SARS-CoV-2 Nucleocapsid proteins.

Multiplex electrochemical biosensors have been used for eliminating the matrix effect in complex bodily fluids or enabling the detection of two or more bioanalytes, overall resulting in more sensitive assays and accurate diagnostics. Many electrochemical biosensors lack reliable and low-cost multiplexing to meet the requirements of point-of-care detection due to either limited functional biosensors for multi-electrode detection or incompatible readout systems. We developed a new dual electrochemical biosensing unit accompanied by a customized potentiostat to address the unmet need for point-of-care multi-electrode electrochemical biosensing. The two-working electrode system was developed using screen-printing of a carboxyl-rich nanomaterial containing ink, with both working electrodes offering active sites for recognition of bioanalytes. The low-cost bi-potentiostat system (∼$80) was developed and customized specifically to the bi-electrode design and used for rapid, repeatable, and accurate measurement of electrochemical impedance spectroscopy signals from the dual biosensor. This binary electrochemical data acquisition (Bi-ECDAQ) system accurately and selectively detected SARS-CoV-2 Nucleocapsid protein (N-protein) in both spiked samples and clinical nasopharyngeal swab samples of COVID-19 patients within 30 min. The two working electrodes offered the limit of detection of 116 fg/mL and 150 fg/mL, respectively, with the dynamic detection range of 1-10,000 pg/mL and the sensitivity range of 2744-2936 Ω mL/pg.mm2 for the detection of N-protein. The potentiostat performed comparable or better than commercial Autolab potentiostats while it is significantly lower cost. The open-source Bi-ECDAQ presents a customizable and flexible approach towards addressing the need for rapid and accurate point-of-care electrochemical biosensors for the rapid detection of various diseases.

Highly Stable Buffer-Based Zinc Oxide/Reduced Graphene Oxide Nanosurface Chemistry for Rapid Immunosensing of SARS-CoV-2 Antigens.

The widespread and long-lasting effect of the COVID-19 pandemic has called attention to the significance of technological advances in the rapid diagnosis of SARS-CoV-2 virus. This study reports the use of a highly stable buffer-based zinc oxide/reduced graphene oxide (bbZnO/rGO) nanocomposite coated on carbon screen-printed electrodes for electrochemical immuno-biosensing of SARS-CoV-2 nuelocapsid (N-) protein antigens in spiked and clinical samples. The incorporation of a salt-based (ionic) matrix for uniform dispersion of the nanomixture eliminates multistep nanomaterial synthesis on the surface of the electrode and enables a stable single-step sensor nanocoating. The immuno-biosensor provides a limit of detection of 21 fg/mL over a linear range of 1-10 000 pg/mL and exhibits a sensitivity of 32.07 ohms·mL/pg·mm2 for detection of N-protein in spiked samples. The N-protein biosensor is successful in discriminating positive and negative clinical samples within 15 min, demonstrating its proof of concept used as a COVID-19 rapid antigen test.

Gut-on-chip for ecological and causal human gut microbiome research.

There is a growing interest to understand if and how the gut microbiome is causally linked to the pathogenesis and/or progression of diseases. While in vitro cell line models are commonly used for studying specific aspects of the host-microbe interaction, gnotobiotic murine models are considered the preferred platform for studying causality in microbiome research. Nevertheless, findings from animal studies provide limited opportunity for delineating various areas of interest to the human gut microbiome research. Gut-on-chips are biomimetics recapitulating intestinal physiology which enable investigation of bidirectional effects of the host and microbiome. We posit that they could advance causal and ecological gut microbiome research in three major areas: (i) diet-microbiome and drug-microbiome interaction; (ii) microbiome-targeted therapeutics pharmacoecology; and (iii) mechanistic studies of gut microbiome and microbiome-targeted intervention in extraintestinal pathologies.

Immuno-biosensor on a chip: a self-powered microfluidic-based electrochemical biosensing platform for point-of-care quantification of proteins.

The realization of true point-of-care (PoC) systems profoundly relies on integrating the bioanalytical assays into "on-chip" fluid handing platforms, with autonomous performance, reproducible functionality, and capacity in scalable production. Specifically for electrochemical immuno-biosensing, the complexity of the procedure used for ultrasensitive protein detection using screen-printed biosensors necessitates a lab-centralized practice, hindering the path towards near-patient use. This work develops a self-powered microfluidic chip that automates the entire assay of electrochemical immuno-biosensing, enabling controlled and sequential delivery of the biofluid sample and the sensing reagents to the surface of the embedded electrochemical biosensor. Without any need for active fluid handling, this novel sample-to-result testing kit offers antibody-antigen immunoreaction within 15 min followed by the subsequent automatic washing, redox probe delivery, and electrochemical signal recording. The redox molecules ([Fe(CN)6]3-/4-) are pre-soaked and dried in fiber and embedded inside the chip. The dimensions of the fluidic design and the parameters of the electrochemical bioassay are optimized to warrant a consistent and reproducible performance of the autonomous sensing device. The uniform diffusion of the dried redox into the injected solution and its controlled delivery onto the biosensor are modeled via a two-phase flow computational fluid dynamics simulation, determining the suitable time for electrochemical signal measurement from the biosensor. The microfluidic chip performs well with both water-based fluids and human plasma with the optimized sample volume to offer a proof-of-concept ultrasensitive biosensing of SARS-CoV-2 nucleocapsid proteins spiked in phosphate buffer saline within 15 min. The on-chip N-protein biosensing demonstrates a linear detection range of 10 to 1000 pg mL-1 with a limit of detection of 3.1 pg mL-1. This is the first self-powered microfluidic-integrated electrochemical immuno-biosensor that promises quantitative and ultrasensitive PoC biosensing. Once it is modified for its design and dimensions, it can be further used for autonomous detection of one or multiple proteins in diverse biofluid samples.

Label-Free Isolation of Exosomes Using Microfluidic Technologies.

Exosomes are cell-derived structures packaged with lipids, proteins, and nucleic acids. They exist in diverse bodily fluids and are involved in physiological and pathological processes. Although their potential for clinical application as diagnostic and therapeutic tools has been revealed, a huge bottleneck impeding the development of applications in the rapidly burgeoning field of exosome research is an inability to efficiently isolate pure exosomes from other unwanted components present in bodily fluids. To date, several approaches have been proposed and investigated for exosome separation, with the leading candidate being microfluidic technology due to its relative simplicity, cost-effectiveness, precise and fast processing at the microscale, and amenability to automation. Notably, avoiding the need for exosome labeling represents a significant advance in terms of process simplicity, time, and cost as well as protecting the biological activities of exosomes. Despite the exciting progress in microfluidic strategies for exosome isolation and the countless benefits of label-free approaches for clinical applications, current microfluidic platforms for isolation of exosomes are still facing a series of problems and challenges that prevent their use for clinical sample processing. This review focuses on the recent microfluidic platforms developed for label-free isolation of exosomes including those based on sieving, deterministic lateral displacement, field flow, and pinched flow fractionation as well as viscoelastic, acoustic, inertial, electrical, and centrifugal forces. Further, we discuss advantages and disadvantages of these strategies with highlights of current challenges and outlook of label-free microfluidics toward the clinical utility of exosomes.

Numerical and experimental analysis of a hybrid material acoustophoretic device for manipulation of microparticles.

Acoustophoretic microfluidic devices have been developed for accurate, label-free, contactless, and non-invasive manipulation of bioparticles in different biofluids. However, their widespread application is limited due to the need for the use of high quality microchannels made of materials with high specific acoustic impedances relative to the fluid (e.g., silicon or glass with small damping coefficient), manufactured by complex and expensive microfabrication processes. Soft polymers with a lower fabrication cost have been introduced to address the challenges of silicon- or glass-based acoustophoretic microfluidic systems. However, due to their small acoustic impedance, their efficacy for particle manipulation is shown to be limited. Here, we developed a new acoustophoretic microfluid system fabricated by a hybrid sound-hard (aluminum) and sound-soft (polydimethylsiloxane polymer) material. The performance of this hybrid device for manipulation of bead particles and cells was compared to the acoustophoretic devices made of acoustically hard materials. The results show that particles and cells in the hybrid material microchannel travel to a nodal plane with a much smaller energy density than conventional acoustic-hard devices but greater than polymeric microfluidic chips. Against conventional acoustic-hard chips, the nodal line in the hybrid microchannel could be easily tuned to be placed in an off-center position by changing the frequency, effective for particle separation from a host fluid in parallel flow stream models. It is also shown that the hybrid acoustophoretic device deals with smaller temperature rise which is safer for the actuation of bioparticles. This new device eliminates the limitations of each sound-soft and sound-hard materials in terms of cost, adjusting the position of nodal plane, temperature rise, fragility, production cost and disposability, making it desirable for developing the next generation of economically viable acoustophoretic products for ultrasound particle manipulation in bioengineering applications.

Engineering a 3D human intracranial aneurysm model using liquid-assisted injection molding and tuned hydrogels.

Physiologically relevant intracranial aneurysm (IA) models are crucially required to facilitate testing treatment options for IA. Herein, we report the development of a new in vitro tissue-engineered platform, which recapitulates the microenvironment, structure, and cellular complexity of native human IA. A new modified liquid-assisted injection molding technique was developed to fabricate a three-dimensional hollow IA model with clinically relevant IA dimensions within a mechanically tuned Gelatin Methacryloyl (GelMA) hydrogel. An endothelium lining was created inside the IA model by culturing human umbilical vein endothelial cells over pre-cultured human brain vascular smooth muscle cells. These cellularized IA models were subjected to medium perfusion at flow rates between 6.3 and 15.75 mL/min for inducing biomimetic vessel wall shear stress (10-25 dyn/cm2) to the cells for ten days. Both cell types maintained their secretome profiles and showed more than 96% viability, demonstrating the biocompatibility of the hydrogel during perfusion cell culture at such flow rates. Based on the characterized viscoelastic properties of the GelMA hydrogel and with the aid of a fluid-structure interaction model, the capability of the IA model in predicting the response of the IA to different fluid flow profiles was mathematically shown. With physiologically relevant behavior, our developed in vitro human IA model could allow researchers to better understand the pathophysiology and treatment of IA. STATEMENT OF SIGNIFICANCE: A three-dimensional intracranial aneurysm (IA) tissue model recapitulating the microenvironment, structure, and cellular complexity of native human IA was developed. • An endothelium lining was created inside the IA model over pre-cultured human brain vascular smooth muscle cells over at least 10-day successful culture. • The cells maintained their secretome profiles, demonstrating the biocompatibility of hydrogel during a long-term perfusion cell culture. • The IA model showed its capability in predicting the response of IA to different fluid flow profiles. • The cells in the vessel region behaved differently from cells in the aneurysm region due to alteration in hemodynamic shear stress. • The IA model could allow researchers to better understand the pathophysiology and treatment options of IA.

An ensemble learning approach to digital corona virus preliminary screening from cough sounds.

This work develops a robust classifier for a COVID-19 pre-screening model from crowdsourced cough sound data. The crowdsourced cough recordings contain a variable number of coughs, with some input sound files more informative than the others. Accurate detection of COVID-19 from the sound datasets requires overcoming two main challenges (i) the variable number of coughs in each recording and (ii) the low number of COVID-positive cases compared to healthy coughs in the data. We use two open datasets of crowdsourced cough recordings and segment each cough recording into non-overlapping coughs. The segmentation enriches the original data without oversampling by splitting the original cough sound files into non-overlapping segments. Splitting the sound files enables us to increase the samples of the minority class (COVID-19) without changing the feature distribution of the COVID-19 samples resulted from applying oversampling techniques. Each cough sound segment is transformed into six image representations for further analyses. We conduct extensive experiments with shallow machine learning, Convolutional Neural Network (CNN), and pre-trained CNN models. The results of our models were compared to other recently published papers that apply machine learning to cough sound data for COVID-19 detection. Our method demonstrated a high performance using an ensemble model on the testing dataset with area under receiver operating characteristics curve = 0.77, precision = 0.80, recall = 0.71, F1 measure = 0.75, and Kappa = 0.53. The results show an improvement in the prediction accuracy of our COVID-19 pre-screening model compared to the other models.

A tuned gelatin methacryloyl (GelMA) hydrogel facilitates myelination of dorsal root ganglia neurons in vitro.

Investigating axonal myelination by Schwann cells (SCs) is crucial for understanding mechanisms underlying demyelination and remyelination, which may help gain insights into incurable disorders like neurodegenerative diseases. In this study, a gelatin-based hydrogel, gelatin methacryloyl (GelMA), was optimized to achieve the biocompatibility, porosity, mechanical stability, and degradability needed to provide high cell viability for dorsal root ganglia (DRG) neurons and SCs, and to enable their long-term coculture needed for myelination studies. The results of cell viability, neurite elongation, SC function and maturation, SC-axon interaction, and myelination were compared with two other commonly used substrates, namely collagen and Poly-d Lysine (PDL). The tuned GelMA constructs (Young's modulus of 32.6 ± 1.9 kPa and the median value of pore size of 10.3 µm) enhanced single axon generation (unlike collagen) and promoted the interaction of DRG neurons and SCs (unlike PDL). While DRG cells exhibited relatively higher viability on PDL after 48 h, i.e., 83.8%, the cells had similar survival rate on GelMA and collagen substrates, 66.7% and 61.5%, respectively. Further adjusting the hydrogel properties to achieve two distinct ranges of relatively small and large pores supported SCs to extend their processes freely and enabled physical contact with and wrapping around their corresponding axons. Staining the cells with myelin basic protein (MBA) and myelin-associated glycoprotein (MAG) revealed enhanced myelination on GelMA hydrogel compared to PDL and collagen. Moreover, the engineered porosity enhanced DRGs and SCs attachments and flexibility of movement across the substrate. This engineered hydrogel structure can now be further explored to model demyelination in neurodegenerative diseases, as well as to study the effects of various compounds on myelin regeneration.

Microfluidic-based processors and circuits design.

Droplets produced within microfluidics have not only attracted the attention of researchers to develop complex biological, industrial and clinical testing systems but also played a role as a bit of data. The flow of droplets within a network of microfluidic channels by stimulation of their movements, trajectories, and interaction timing, can provide an opportunity for preparation of complex and logical microfluidic circuits. Such mechanical-based circuits open up avenues to mimic the logic of electrical circuits within microfluidics. Recently, simple microfluidic-based logical elements such as AND, OR, and NOT gates have been experimentally developed and tested to model basic logic conditions in laboratory settings. In this work, we develop new microfluidic networks, control the shape of channels and speed of droplet movement, and regulate the size of bubbles in order to extend the logical elements to six new logic gates, including AND/OR type 1, AND/OR type 2, NOT type 1, NOT type 2, Flip-Flop, Synchronizer, and a parametric model of T-junction as a bubble generator. We further designed and simulated a novel microfluidic Decoder 1 to 2, a Decoder 2 to 4, and a microfluidic circuit that combines several individual logic gates into one complex circuit. Further fabrication and experimental testing of these newly introduced logic gates within microfluidics enable implementing complex circuits in high-throughput microfluidic platforms for tissue engineering, drug testing and development, and chemical synthesis and process design.

A simple, low cost and reusable microfluidic gradient strategy and its application in modeling cancer invasion.

Microfluidic chemical gradient generators enable precise spatiotemporal control of chemotactic signals to study cellular behavior with high resolution and reliability. However, time and cost consuming preparation steps for cell adhesion in microchannels as well as requirement of pumping facilities usually complicate the application of the microfluidic assays. Here, we introduce a simple strategy for preparation of a reusable and stand-alone microfluidic gradient generator to study cellular behavior. Polydimethylsiloxane (PDMS) is directly mounted on the commercial polystyrene-based cell culture surfaces by manipulating the PDMS curing time to optimize bonding strength. The stand-alone strategy not only offers pumpless application of this microfluidic device but also ensures minimal fluidic pressure and consequently a leakage-free system. Elimination of any surface treatment or coating significantly facilitates the preparation of the microfluidic assay and offers a detachable PDMS microchip which can be reused following to a simple cleaning and sterilization step. The chemotactic signal in our microchip is further characterized using numerical and experimental evaluations and it is demonstrated that the device can generate both linear and polynomial signals. Finally, the feasibility of the strategy in deciphering cellular behavior is demonstrated by exploring cancer cell migration and invasion in response to chemical stimuli. The introduced strategy can significantly decrease the complexity of the microfluidic chemotaxis assays and increase their throughput for various cellular and molecular studies.

In-vitro tumor microenvironment models containing physical and biological barriers for modelling multidrug resistance mechanisms and multidrug delivery strategies.

The complexity and heterogeneity of the three-dimensional (3D) tumor microenvironment have brought challenges to tumor studies and cancer treatment. The complex functions and interactions of cells involved in tumor microenvironment have led to various multidrug resistance (MDR) and raised challenges for cancer treatment. Traditional tumor models are limited in their ability to simulate the resistance mechanisms and not conducive to the discovery of multidrug resistance and delivery processes. New technologies for making 3D tissue models have shown the potential to simulate the 3D tumor microenvironment and identify mechanisms underlying the MDR. This review overviews the main barriers against multidrug delivery in the tumor microenvironment and highlights the advances in microfluidic-based tumor models with the success in simulating several drug delivery barriers. It also presents the progress in modeling various genetic and epigenetic factors involved in regulating the tumor microenvironment as a noticeable insight in 3D microfluidic tumor models for recognizing multidrug resistance and delivery mechanisms. Further correlation between the results obtained from microfluidic drug resistance tumor models and the clinical MDR data would open up avenues to gain insight into the performance of different multidrug delivery treatment strategies.

Emerging technologies and commercial products in exosome-based cancer diagnosis and prognosis.

Academic and industrial groups worldwide have reported technological advances in exosome-based cancer diagnosis and prognosis. However, the potential translation of these emerging technologies for research and clinical settings remains unknown. This work overviews the role of exosomes in cancer diagnosis and prognosis, followed by a survey on emerging exosome technologies, particularly microfluidic advances for the isolation and detection of exosomes in cancer research. The advantages and drawbacks of each of the technologies used for the isolation, detection and engineering of exosomes are evaluated to address their clinical challenges for cancer diagnosis and prognosis. Furthermore, commercial platforms for exosomal detection and analysis are introduced, and their performance and impact on cancer diagnosis and prognosis are assessed. Also, the risks associated with the further development of the next generation of exosome devices are discussed. The outcome of this work could facilitate recognizing deliverable Exo-devices and technologies with unprecedented functionality and predictable manufacturability for the next-generation of cancer diagnosis and prognosis.