A deep-reinforcement learning approach for optimizing homogeneous droplet routing in digital microfluidic biochips

Over the past two decades,digital microfluidic biochips have been in much demand for safety-critical and biomedical applications and increasingly important in point-of-care analysis,drug discovery,and immunoassays,among other areas.However,for complex bioassays,finding routes for the transportation of droplets in an electrowetting-on-dielectric digital biochip while maintaining their discreteness is a challenging task.In this study,we propose a deep reinforcement learning-based droplet routing technique for digital microfluidic biochips.The technique is implemented on a distributed architecture to optimize the possible paths for predefined source–target pairs of droplets.The actors of the technique calculate the possible routes of the source–target pairs and store the experience in a replay buffer,and the learner fetches the experiences and updates the routing paths.The proposed algorithm was applied to benchmark suitesⅠand Ⅲ as two different test benches,and it achieved significant improvements over state-of-the-art techniques.

A digital microfluidic single-cell manipulation systemoptimized by extending-depth-of-field device

Microfuidic systems have been widely utilized in high-throughput biology analysis,but thedificulties in iquid manipulation and cell cultivation limit its application.This work has developed a new digital microfluidic(DMF)system for on-demand droplet control.By adopting anextending-depth-of-field(EDoF)phase modulator to the optical system,the entire depth of themicrofluidic channel can be covered in one image without any refocusing process,ensuring that 95%of the particles in the droplet are captured within three shots together with shaking pro-cesses.With this system,suspension droplets are generated and droplets containing only oneyeast cll can be recognized,then each single cell is cultured in the array of the chip.Byobservingtheir growth in cell numbers and the green fluorescence protein(GFP)production via fluorescence imaging,the single cell with the highest production can be identified.The results haveproved the heterogeneity of yeast cells,and showed that the combined system can be applied forrapid single-cell sorting,cultivation,and analysis.

Numerical Study of the Evaporation Effects on the Microdroplet Dynamics in Digital Microfluidic Biochips

In this paper, an electrohydrodynamic approach is used to model and study dynamics of evaporating microdroplets in digital microfluidic systems. A numerical eleetrohydrodynamic approach is used to calculate the driving force and shear force （due to the walls）. Effects of contact line pinning is considered by adding a three-phase contact line force, and also considering dynamic contact angle which modifies the mierodroplet boundary conditions. Since air is used as the filler fluid, the drag force is neglected. Although energy equation is not solved （constant temperature assumption）, effects of the evaporation is considered from two aspects： It is shown that an additional force is needed to balance the dynamic equation of the mierodroplet motion. Also, at each time step the microdroplet interface has to be deformed due to the change in the microdroplet radius. Important findings of the proposed model includes the transient velocity and displacement of the microdroplet as well as the driving and opposing forces acting on the microdroplet as functions of time. It is shown that mass loss due to evaporation tends to accelerate the droplet; whereas the competitive effect of the reduced driving force decelerates the droplet at the end of motion. The modeling results indicate that evaporation plays a crucial role in microdroplet motion by changing the force balance and the microdroplet boundary condition.

DMF-scMT-seq linking methylome and transcriptome within single cells with digital microfluidics

Single-cell joint analysis of methylome and transcriptome reveals how the methylation regulates the transcriptional activity.However,traditional bench-top protocols for single-cell DNA methylation and RNA transcription co-detection are laborintensive,cost-ineffective and contaminant-prone.Herein,we establish the DMF-sc MT-seq,a highly-efficient and cost-effective method to simultaneously analyze single-cell DNA methylation and transcriptional activity based on digital microfluidics.DMFsc MT-seq automates the workflow of single-cell isolation,cellular hypotonic lysis,nucleic acid separation and methylome/transcriptome library construction in a contactless and addressable way.The system ensures high accuracy(R>0.85),high gene detection ability(14,697 genes per cell at 4 million sequencing depth),and high CpG coverage(677,198 CpG sites per cell at 1million sequencing depth).By using DMF-sc MT-seq,the relationship of DNA methylation and RNA transcription under different genomic contexts is resolved.We further apply DMF-sc MT-seq to study the dynamics of transcription regulation with methylation-inhibiting anti-tumor Decitabine,and identify the methylated promoter/gene body driven genes in response to Decitabine treatment.DMF-sc MT-seq facilitates the construction of the correlation of DNA methylation and transcriptional activity at the single-cell level in a flexible,sensitive and accurate way,which is anticipated to be a powerful tool in studying single-cell biological systems.

An automated nucleic acid detection platform using digital microfluidics with an optimized Cas12a system

Outbreaks of both influenza virus and the novel coronavirus SARS-CoV-2 are serious threats to human health and life. It is very important to establish a rapid, accurate test with large-scale detection potential to prevent the further spread of the epidemic. An optimized RPA-Cas12a-based platform combined with digital microfluidics(DMF), the RCD platform, was established to achieve the automated, rapid detection of influenza viruses and SARS-CoV-2. The probe in the RPA-Cas12a system was optimized to produce maximal fluorescence to increase the amplification signal. The reaction droplets in the platform were all at the microliter level and the detection could be accomplished within 30 min due to the effective mixing of droplets by digital microfluidic technology. The whole process from amplification to recognition is completed in the chip, which reduces the risk of aerosol contamination. One chip can contain multiple detection reaction areas, offering the potential for customized detection.The RCD platform demonstrated a high level of sensitivity, specificity(no false positives or negatives), speed(≤30 min),automation and multiplexing. We also used the RCD platform to detect nucleic acids from influenza patients and COVID-19 patients. The results were consistent with the findings of q PCR. The RCD platform is a one-step, rapid, highly sensitive and specific method with the advantages of digital microfluidic technology, which circumvents the shortcomings of manual operation. The development of the RCD platform provides potential for the isothermal automatic detection of nucleic acids during epidemics.

Digital microfluidics： A promising technique for biochemical applications

Digital microfluidics （DMF） is a versatile microfluidics technology that has significant application potential in the areas of automation and miniaturization. In DME discrete droplets containing samples and reagents are controlled to implement a series of operations via electrowetting-on-dielectric. This process works by apply- ing electrical potentials to an array of electrodes coated with a hydrophobic dielectric layer. Unlike microchannels, DMF facilitates precise control over multiple reaction processes without using complex pump, microvalve, and tubing networks. DMF also presents other distinct features, such as portability, less sample consumption, shorter chemical reaction time, flexibility, and easier combination with other technology types. Due to its unique advantages, DMF has been applied to a broad range of fields （e.g., chemistry, biology, medicine, and environment）. This study reviews the basic principles of droplet actuation, configuration design, and fabrication of the DMF device, as well as discusses the latest progress in DMF from the biochemistry perspective.

Intelligent droplet tracking with correlation filters for digital microfluidics

Tracking the movement of droplets in digital microfluidics is essential to improve its control stability and obtain dynamic information for its applications such as point-of-care testing,environment monitoring and chemical synthesis.Herein,an intelligent,accurate and fast droplet tracking method based on machine vision is developed for applications of digital microfluidics.To continuously recognize the transparent droplets in real-time and avoid the interferes from background patterns or inhomogeneous illumination,we introduced the correlation filter tracker,enabling online learning of the multi-features of the droplets in Fourier domain.Results show the proposed droplet tracking method could accurately locate the droplets.We also demonstrated the capacity of the proposed method for estimation of the droplet velocity as faster as 20 mm/s,and its application in online monitoring the Griess reaction for both colorimetric assay of nitrite and study of reaction kinetics.

On-site low-power sensing nodes for distributed monitoring of heavy metal ions in water

Heavy metal pollution in water environments poses a great threat to public health and to the ecological environment due to its high toxicity and non-degradability.However,many existing detection methods require laboratory-based bulky instruments and time-consuming manual operations.Although some on-site systems exist,they are difficult to deploy on a large scale owing to their large size and high cost.Here,we report a sensing node featuring low power consumption and low cost,achieved by integrating microsensor,microfluidic,and electronic modules into a compact size for automatic and scalable heavy metal pollution monitoring.Digital microfluidic and electrochemical sensing modules are integrated on a chip,thereby combining the procedures of sample pretreatment,electrochemical sensing,and waste removal for automatic and continuous monitoring.The feasibility of the platform is demonstrated by Pb2+detection in tap water.With a 3500 mAh battery,the compact sensing node could work for several years in principle.There is scope for further improvements to the system in terms of wider functionality and reductions in size,power consumption,and cost.The sensing node presented here is a strong candidate for distributed monitoring of water quality as an Internet-of-Things application.

Transporting droplets through surface anisotropy

This review article examines digital microfluidic systems that manipulate droplets through surface anisotropy.These systems are categorized as surface tension driven or contact line driven.Surface tension driven systems include electrowetting on dielectric,Marangoni flow on microheater arrays,and chemical gradient surfaces,whereas contact line driven systems include anisotropic ratchet conveyors,nanostructured Parylene ratchets,and tilted pillar arrays.This article describes the operating principles and outlines the fabrication procedures for each system.We also present new equations that unify several previous models of contact line driven systems.The strengths and weaknesses of each system are compared,with a focus on their ability to perform the generation,switching,fusion,and fission of droplets.Finally,we discuss current and potential future applications of these systems.