Label-free and amplification-free viral RNA quantification from primate biofluids using a trapping-assisted optofluidic nanopore platform.

Viral outbreaks can cause widespread disruption, creating the need for diagnostic tools that provide high performance and sample versatility at the point of use with moderate complexity. Current gold standards such as PCR and rapid antigen tests fall short in one or more of these aspects. Here, we report a label-free and amplification-free nanopore sensor platform that overcomes these challenges via direct detection and quantification of viral RNA in clinical samples from a variety of biological fluids. The assay uses an optofluidic chip that combines optical waveguides with a fluidic channel and integrates a solid-state nanopore for sensing of individual biomolecules upon translocation through the pore. High specificity and low limit of detection are ensured by capturing RNA targets on microbeads and collecting them by optical trapping at the nanopore location where targets are released and rapidly detected. We use this device for longitudinal studies of the viral load progression for Zika and Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infections in marmoset and baboon animal models, respectively. The up to million-fold trapping-based target concentration enhancement enables amplification-free RNA quantification across the clinically relevant concentration range down to the assay limit of RT-qPCR as well as cases in which PCR failed. The assay operates across all relevant biofluids, including semen, urine, and whole blood for Zika and nasopharyngeal and throat swab, rectal swab, and bronchoalveolar lavage for SARS-CoV-2. The versatility, performance, simplicity, and potential for full microfluidic integration of the amplification-free nanopore assay points toward a unique approach to molecular diagnostics for nucleic acids, proteins, and other targets.

Nano/microfluidic device for high-throughput passive trapping of nanoparticles.

We present a design and a fabrication method for devices designed for rapid collection of nanoparticles in a fluid. The design uses nanofluidic channels as a passive size-based barrier trap to isolate particles near a central point in the channel, which is also covered by a thin membrane. Particles that enter the collection region are trapped with 100% efficiency within a 6-12 µm radius from a central point. Flow rates for particle-free fluid range from 1.88 to 3.69 nl/s for the pressure and geometries tested. Particle trapping tests show that high trapped particle counts significantly impact flow rates. For suspensions as dilute as 30-300 aM (20-200 particles/µl), 8-80 particles are captured within 500 s.

Transcranial Magnetic Stimulation in Bipolar II Disorder Treatment: A Case Report.

The objective of this case report is to describe and document the use of transcranial magnetic stimulation (TMS) to aid in the treatment of bipolar II disorder. A 35-year-old male with a past medical history of attention-deficit/hyperactivity disorder (ADHD), post-traumatic stress disorder (PTSD), severe depression, and bipolar II disorder was presented to an outpatient psychiatric clinic 1.5 years after his initial TMS treatment for TMS maintenance therapy. He reported feeling depressed, brain fogginess, loss of concentration, fatigue, and constant changes in moods. He had tried multiple antidepressants and antipsychotics, seen several therapists, and underwent electroconvulsive therapy in 2014 with no improvement. In August 2021, he underwent the standard TMS protocol with 36 treatments and noticed significant improvement in his symptoms. He followed up with his psychiatrist who placed him on quetiapine 400 mg, lurasidone 120 mg, topiramate 100 mg, Adderall 20 mg, Wellbutrin 150 mg, propranolol 20 mg, and Klonopin 0.5 mg for management. However, after starting these medications, he noticed a loss of concentration, not being able to think straight, fatigue, depression, and a change in moods. In January 2023, the patient underwent maintenance TMS treatment with theta bursts (TBS). The treatment protocol consisted of 10 sessions for 3 ½ minutes each, 20 trains, 10 bursts, and eight seconds between intervals. He completed his treatment and reported feeling great and like himself again. Two weeks following treatment, he reported that his brain fog had resolved, hypomanic episodes had lessened, and depressive moods had been occurring less often. Due to improvement, topiramate and lurasidone were discontinued and the patient will continue with monthly follow-ups to monitor his progress. TMS appears to be a promising treatment option for bipolar disorder.

Comparison of Illumination Methods for Flow-Through Optofluidic Biosensors.

Optofluidic biosensors have become an important medical diagnostic tool because they allow for rapid, high-sensitivity testing of small samples compared to standard lab testing. For these devices, the practicality of use in a medical setting depends heavily on both the sensitivity of the device and the ease of alignment of passive chips to a light source. This paper uses a model previously validated by comparison to physical devices to compare alignment, power loss, and signal quality for windowed, laser line, and laser spot methods of top-down illumination.

Flow-through charge detection mass spectrometry to categorize micron-sized particles.

This paper outlines the use of charge detection mass spectrometry to simultaneously measure the charge and mass of micron-sized particles. In a flow-through instrument, the detection of charge was achieved through charge induction onto cylindrical electrodes that connect to a differential amplifier. Mass was determined by particle acceleration under the influence of an electric field. Particles ranging from 30 to 400 fg (3 to 7 µm diameter) were tested. The detector design can measure particle mass within 10% accuracy for particles up to 620 fg with total charge ranging from 500e- to 56 ke-. This charge and mass range are expected to be relevant for dust on Mars.

Machine learning at the edge for AI-enabled multiplexed pathogen detection.

Multiplexed detection of biomarkers in real-time is crucial for sensitive and accurate diagnosis at the point of use. This scenario poses tremendous challenges for detection and identification of signals of varying shape and quality at the edge of the signal-to-noise limit. Here, we demonstrate a robust target identification scheme that utilizes a Deep Neural Network (DNN) for multiplex detection of single particles and molecular biomarkers. The model combines fast wavelet particle detection with Short-Time Fourier Transform analysis, followed by DNN identification on an AI-specific edge device (Google Coral Dev board). The approach is validated using multi-spot optical excitation of Klebsiella Pneumoniae bacterial nucleic acids flowing through an optofluidic waveguide chip that produces fluorescence signals of varying amplitude, duration, and quality. Amplification-free 3× multiplexing in real-time is demonstrated with excellent specificity, sensitivity, and a classification accuracy of 99.8%. These results show that a minimalistic DNN design optimized for mobile devices provides a robust framework for accurate pathogen detection using compact, low-cost diagnostic devices.

Adaptive time modulation technique for multiplexed on-chip particle detection across scales.

Integrated optofluidic biosensors have demonstrated ultrasensitivity down to single particle detection and attomolar target concentrations. However, a wide dynamic range is highly desirable in practice and can usually only be achieved by using multiple detection modalities or sacrificing linearity. Here, we demonstrate an analysis technique that uses temporal excitation at two different time scales to simultaneously enable digital and analog detection of fluorescent targets. We demonstrated the seamless detection of nanobeads across eight orders of magnitude from attomolar to nanomolar concentration. Furthermore, a combination of spectrally varying modulation frequencies and a closed-loop feedback system that provides rapid adjustment of excitation laser powers enables multiplex analysis in the presence of vastly different concentrations. We demonstrated this ability to detect across scales via an analysis of a mixture of fluorescent nanobeads at femtomolar and picomolar concentrations. This technique advances the performance and versatility of integrated biosensors, especially toward point-of-use applications.

Optofluidic Particle Manipulation: Optical Trapping in a Thin-Membrane Microchannel.

We demonstrate an optofluidic device which utilizes the optical scattering and gradient forces for particle trapping in microchannels featuring 300 nm thick membranes. On-chip waveguides are used to direct light into microfluidic trapping channels. Radiation pressure is used to push particles into a protrusion cavity, isolating the particles from liquid flow. Two different designs are presented: the first exclusively uses the optical scattering force for particle manipulation, and the second uses both scattering and gradient forces. Trapping performance is modeled for both cases. The first design, referred to as the orthogonal force design, is shown to have a 80% capture efficiency under typical operating conditions. The second design, referred to as the gradient force design, is shown to have 98% efficiency under the same conditions.

Optofluidic Particle Manipulation Platform with Nanomembrane.

We demonstrate a method for fabricating and utilizing an optofluidic particle manipulator on a silicon chip that features a 300 nm thick silicon dioxide membrane as part of a microfluidic channel. The fabrication method is based on etching silicon channels and converting the walls to silicon dioxide through thermal oxidation. Channels are encapsulated by a sacrificial polymer which fills the length of the fluid channel by way of spontaneous capillary action. The sacrificial material is then used as a mold for the formation of a nanoscale, solid-state, silicon dioxide membrane. The hollow channel is primarily used for fluid and particle transport but is capable of transmitting light over short distances and utilizes radiation pressure for particle trapping applications. The optofluidic platform features solid-core ridge waveguides which can direct light on and off of the silicon chip and intersect liquid channels. Optical loss values are characterized for liquid and solid-core structures and at interfaces. Estimates are provided for the optical power needed to trap particles of various sizes.

Fast custom wavelet analysis technique for single molecule detection and identification.

Many sensors operate by detecting and identifying individual events in a time-dependent signal which is challenging if signals are weak and background noise is present. We introduce a powerful, fast, and robust signal analysis technique based on a massively parallel continuous wavelet transform (CWT) algorithm. The superiority of this approach is demonstrated with fluorescence signals from a chip-based, optofluidic single particle sensor. The technique is more accurate than simple peak-finding algorithms and several orders of magnitude faster than existing CWT methods, allowing for real-time data analysis during sensing for the first time. Performance is further increased by applying a custom wavelet to multi-peak signals as demonstrated using amplification-free detection of single bacterial DNAs. A 4x increase in detection rate, a 6x improved error rate, and the ability for extraction of experimental parameters are demonstrated. This cluster-based CWT analysis will enable high-performance, real-time sensing when signal-to-noise is hardware limited, for instance with low-cost sensors in point of care environments.

FPGA Integrated Optofluidic Biosensor for Real-Time Single Biomarker Analysis.

Integrated optofluidic biosensors can fill the need for sensitive, amplification-free, multiplex single molecule detection which is relevant for containing the spread of infectious diseases such as COVID-19. Here, we demonstrate a rapid sample-to-answer scheme that uses a field programmable gate array (FPGA) to enable live monitoring of single particle fluorescence analysis on an optofluidic chip. Fluorescent nanobeads flowing through a micro channel are detected with 99% accuracy and particle concentrations in clinically relevant ranges from 3.4×104 to 3.4 × 106/ml are determined within seconds to a few minutes without the need for post-experiment data extraction and analysis. In addition, other extract salient experimental parameters such as dynamic flow rate changes can be monitored in real time. The sensor is validated with real-time fluorescence detection of single bacterial plasmid DNA at attomolar concentrations, showing excellent promise for implementation as a point of care (POC) diagnostic tool.

Free-Space Excitation of Optofluidic Devices for Pattern-Based Single Particle Detection.

Optofluidic sensors have enabled single molecule sensing using planar, waveguide dependent multi-spot fluorescence excitation. Here, we demonstrate a new approach to single-particle fluorescence sensing using free-space, top-down illumination of liquid-core antiresonant reflecting optical waveguide (ARROW) devices using two different multi-spot excitation techniques. First, the liquid core ARROW waveguide is excited with a focused beam through a slit pattern milled into an opaque aluminum film, showing comparable performance for single bead fluorescence detection as in-plane, multi-mode interference waveguide based excitation. The second top-down illumination technique images the spot pattern from a Y-splitter SiO2 waveguide chip directly onto the detection device for efficient power utilization and circumventing the need for an opaque cover, producing a further 2.7x improvement in signal-to-noise ratio. The two top-down approaches open up new possibilities for chip-based optical particle sensing with relaxed alignment tolerances.

Optical trapping assisted label-free and amplification-free detection of SARS-CoV-2 RNAs with an optofluidic nanopore sensor.

Ultrasensitive, versatile sensors for molecular biomarkers are a critical component of disease diagnostics and personalized medicine as the COVID-19 pandemic has revealed in dramatic fashion. Integrated electrical nanopore sensors can fill this need via label-free, direct detection of individual biomolecules, but a fully functional device for clinical sample analysis has yet to be developed. Here, we report amplification-free detection of SARS-CoV-2 RNAs with single molecule sensitivity from clinical nasopharyngeal swab samples on an electro-optofluidic chip. The device relies on optically assisted delivery of target carrying microbeads to the nanopore for single RNA detection after release. A sensing rate enhancement of over 2,000x with favorable scaling towards lower concentrations is demonstrated. The combination of target specificity, chip-scale integration and rapid detection ensures the practicality of this approach for COVID-19 diagnosis over the entire clinically relevant concentration range from 104-109 copies/mL.

Comparison of the Dynamic Thermal Gradient to Temperature-Programmed Conditions in Gas Chromatography Using a Stochastic Transport Model.

This paper compares dynamic (i.e., temporally changing) thermal gradient gas chromatography (GC) to temperature-programmed GC using a previously published stochastic transport model to simulate peak characteristics for the separation of C12-C40 hydrocarbons. All comparisons are made using chromatographic conditions that give approximately equal analyte retention times (tR). As shown previously, a static thermal gradient does not improve resolution (Rs) equally for all analytes, which highlights the need for a dynamic thermal gradient. An optimal dynamic thermal gradient should result in constant analyte velocities at any instant in time for those analytes that are actively being separated (i.e., analytes that have low retention factors). The average separation temperature for each analyte is used to determine the thermal gradient profile at different times in the temperature ramp. Because many of the analytes require a similar thermal gradient profile when actively being separated, the thermal gradient profile in this study was held fixed; however, the temperature of the entire thermal gradient was raised over time. From the simulations performed in this study, optimized dynamic thermal gradient conditions are shown to improve Rs by up to 13% over comparative temperature-programmed conditions, even with a perfect injection (i.e., zero injection bandwidth). In the dynamic thermal gradient simulations, all analytes showed improvements in Rs along with slightly shorter tR values compared to simulations for traditional temperature-programmed conditions.

Performance Comparison of Flow-Through Optofluidic Biosensor Designs.

Optofluidic flow-through biosensors are being developed for single particle detection, particularly as a tool for pathogen diagnosis. The sensitivity of the biosensor chip depends on design parameters, illumination format (side vs. top), and flow configuration (parabolic, two- and three-dimensional hydrodynamic focused (2DHF and 3DHF)). We study the signal differences between various combinations of these design aspects. Our model is validated against a sample of physical devices. We find that side-illumination with 3DHF produces the strongest and consistent signal, but parabolic flow devices process a sample volume more quickly. Practical matters of optical alignment are also discussed, which may affect design choice.

Optofluidic Flow-Through Biosensor Sensitivity - Model and Experiment.

We present a model and simulation for predicting the detected signal of a fluorescence-based optical biosensor built from optofluidic waveguides. Typical applications include flow experiments to determine pathogen concentrations in a biological sample after tagging relevant DNA or RNA sequences. An overview of the biosensor geometry and fabrication processes is presented. The basis for the predictive model is also outlined. The model is then compared to experimental results for three different biosensor designs. The model is shown to have similar signal statistics as physical tests, illustrating utility as a pre-fabrication design tool and as a predictor of detection sensitivity.

Recent advances in integrated solid-state nanopore sensors.

The advent of single-molecule probing techniques has revolutionized the biomedical and life science fields and has spurred the development of a new class of labs-on-chip based on powerful biosensors. Nanopores represent one of the most recent and most promising single molecule sensing paradigms that is seeing increased chip-scale integration for improved convenience and performance. Due to their physical structure, nanopores are highly sensitive, require low sample volume, and offer label-free, amplification-free, high-throughput real-time detection and identification of biomolecules. Over the last 25 years, nanopores have been extensively employed to detect a variety of biomolecules with a growing range of applicatons ranging from nucleic acid sequencing to ultrasensitive diagnostics to single-molecule biophysics. Nanopores, in particular those in solid-state membranes, also have the potential for integration with other technologies such as optics, plasmonics, microfluidics, and optofluidics to perform more complex tasks for an ever-expanding demand. A number of breakthrough results using integrated nanopore platforms have already been reported, and more can be expected as nanopores remain the focus of innovative research and are finding their way into commercial instruments. This review provides an overview of different aspects and challenges of nanopore technology with a focus on chip-scale integration of solid-state nanopores for biosensing and bioanalytical applications.

Greatly Enhanced Single Particle Fluorescence Detection Using High Refractive Index Liquid-Core Waveguides.

High sensitivity and easy integration with microfabrication techniques has made silicon photonics one of the leading technologies used to build biosensors for diagnostic applications. Here we introduce a new silicon dioxide based optofluidic platform having a planar solid-core (SC) waveguide orthogonally intersecting a liquid-core (LC) waveguide with high refractive index ZnI2 salt solution as core. This enables both more uniform collection of particle fluorescence by the core mode and its propagation to an off-chip detector. This approach results in ultra-high sensitivity performance, demonstrated by achieving 8X enhancement in signal-to-noise ratio, a 45x increase in detection efficiency, and a 100x lower detection limit of 80 aM of fluorescent nanobeads. This represents a key step towards an ultrasensitive biosensor system for analyzing pathogens at clinical concentrations.

Optofluidic multiplex detection of single SARS-CoV-2 and influenza A antigens using a novel bright fluorescent probe assay.

The urgency for the development of a sensitive, specific, and rapid point-of-care diagnostic test has deepened during the ongoing COVID-19 pandemic. Here, we introduce an ultrasensitive chip-based antigen test with single protein biomarker sensitivity for the differentiated detection of both severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza A antigens in nasopharyngeal swab samples at diagnostically relevant concentrations. The single-antigen assay is enabled by synthesizing a brightly fluorescent reporter probe, which is incorporated into a bead-based solid-phase extraction assay centered on an antibody sandwich protocol for the capture of target antigens. After optimization of the probe release for detection using ultraviolet light, the full assay is validated with both SARS-CoV-2 and influenza A antigens from clinical nasopharyngeal swab samples (PCR-negative spiked with target antigens). Spectrally multiplexed detection of both targets is implemented by multispot excitation on a multimode interference waveguide platform, and detection at 30 ng/mL with single-antigen sensitivity is reported.

Comparison of Static Thermal Gradient to Isothermal Conditions in Gas Chromatography Using a Stochastic Transport Model.

This paper compares static (i.e., temporally unchanging) thermal gradient gas chromatography (GC) to isothermal GC using a stochastic transport model to simulate peak characteristics for the separation of C12-C14 hydrocarbons resulting from variations in injection bandwidth. All comparisons are made using chromatographic conditions that give approximately equal analyte retention times so that the resolution and number of theoretical plates can be clearly compared between simulations. Simulations show that resolution can be significantly improved using a linear thermal gradient along the entire column length. This is mainly achieved by partially compensating for loss in resolution from the increase in mobile phase velocity, which approximates an ideal, basic separation. The slope of the linear thermal gradient required to maximize resolution is a function of the retention parameters, which are specific to each analyte pair; a single static, thermal gradient will not affect all analytes equally. A static, non-linear thermal gradient that creates constant analyte velocities at all column locations provides the largest observed gains in resolution. From the simulations performed in this study, optimized linear thermal gradient conditions are shown to improve the resolution by as much as 8.8% over comparative isothermal conditions, even with a perfect injection (i.e., zero initial bandwidth).