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.

Impact of Tracer Dose Reduction in [18 F]-Labelled Fluorodeoxyglucose-Positron Emission Tomography ([18 F]-FDG)-PET) on Texture Features and Histogram Indices: A Study in Homogeneous Tissues of Phantom and Patient.

BACKGROUND: Histogram indices (HIs) and texture features (TFs) are considered to play an important role in future oncologic PET-imaging and it is unknown how these indices are affected by changes of tracer doses. A randomized undersampling of PET list mode data enables a simulation of tracer dose reduction. We performed a phantom study to compare HIs/TFs of simulated and measured tracer dose reductions and evaluated changes of HIs/TFs in the liver of patients with PETs from simulated reduced tracer doses. Overall, 42 HIs/TFs were evaluated in a NEMA phantom at measured and simulated doses (stepwise reduction of [18 F] from 100% to 25% of the measured dose). [18 F]-FDG-PET datasets of 15 patients were simulated from 3.0 down to 0.5 MBq/kgBW in intervals of 0.25 MBq/kgBW. HIs/TFs were calculated from two VOIs placed in physiological tissue of the right and left liver lobe and linear correlations and coefficients of variation analysis were performed. RESULTS: All 42 TFs did not differ significantly in measured and simulated doses (p > 0.05). Also, 40 TFs showed the same behaviour over dose reduction regarding differences in the same group (measured or simulated), and for 26 TFs a linear behaviour over dose reduction for measured and simulated doses could be validated. Out of these, 13 TFs could be identified, which showed a linear change in TF value in both the NEMA phantom and patient data and therefore should maintain the same informative value when transferred in a dose reduction setting. Out of this Homogeneity 2, Entropy and Zone size non-uniformity are of special interest because they have been described as preferentially considerable for tumour heterogeneity characterization. CONCLUSIONS: We could show that there was no significant difference of measured and simulated HIs/TFs in the phantom study and most TFs reveal a linear behaviour over dose reduction, when tested in homogeneous tissue. This indicates that texture analysis in PET might be robust to dose modulations.

Dual optofluidic distributed feedback dye lasers for multiplexed biosensing applications.

Integrated optofluidic devices have become subjects of high interest for rapid biosensor devices due to their unique ability to combine the fluidic processing of small volumes of microfluidics with the analysis capabilities of photonic structures. By integrating dynamically reconfigurable optofluidic lasers on-chip, complex coupling can be eliminated while further increasing the capabilities of sensors to detect an increasing number of target biomarkers. Here, we report a polydimethylsiloxane-based device with two on-chip fluidic distributed feedback (DFB) laser cavities that are integrated with an orthogonal analyte channel for multiplexed fluorescence excitation. One DFB grating is filled with 4-(dicyanomethylene)-2-methyl-6-(4-dimethylaminostyryl)-4H-pyran dissolved in dimethyl sulfoxide. The second grating is filled with rhodamine 6G dissolved in a diluted ethylene glycol solution. We present characterization of both lasers through analysis of the lasing spectra for spectral narrowing along with a power series to observe threshold behavior. We then demonstrate simultaneous detection of two different fluorescent microbeads as a proof of concept for scalable, single biomarker analysis using on-chip optofluidic lasers.

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.

Open-loop lab-on-a-chip technology enables remote computer science training in Latinx life sciences students.

Despite many interventions, science education remains highly inequitable throughout the world. Among all life sciences fields, Bioinformatics and Computational Biology suffer from the strongest underrepresentation of racial and gender minorities. Internet-enabled project-based learning (PBL) has the potential to reach underserved communities and increase the diversity of the scientific workforce. Here, we demonstrate the use of lab-on-a-chip (LoC) technologies to train Latinx life science undergraduate students in concepts of computer programming by taking advantage of open-loop cloud-integrated LoCs. We developed a context-aware curriculum to train students at over 8,000 km from the experimental site. We showed that this approach was sufficient to develop programming skills and increase the interest of students in continuing careers in Bioinformatics. Altogether, we conclude that LoC-based Internet-enabled PBL can become a powerful tool to train Latinx students and increase the diversity in STEM.

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.

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.

Development of a Hybrid-Imaging-Based Prognostic Index for Metastasized-Melanoma Patients in Whole-Body 18F-FDG PET/CT and PET/MRI Data.

Besides tremendous treatment success in advanced melanoma patients, the rapid development of oncologic treatment options comes with increasingly high costs and can cause severe life-threatening side effects. For this purpose, predictive baseline biomarkers are becoming increasingly important for risk stratification and personalized treatment planning. Thus, the aim of this pilot study was the development of a prognostic tool for the risk stratification of the treatment response and mortality based on PET/MRI and PET/CT, including a convolutional neural network (CNN) for metastasized-melanoma patients before systemic-treatment initiation. The evaluation was based on 37 patients (19 f, 62 ± 13 y/o) with unresectable metastasized melanomas who underwent whole-body 18F-FDG PET/MRI and PET/CT scans on the same day before the initiation of therapy with checkpoint inhibitors and/or BRAF/MEK inhibitors. The overall survival (OS), therapy response, metastatically involved organs, number of lesions, total lesion glycolysis, total metabolic tumor volume (TMTV), peak standardized uptake value (SULpeak), diameter (Dmlesion) and mean apparent diffusion coefficient (ADCmean) were assessed. For each marker, a Kaplan−Meier analysis and the statistical significance (Wilcoxon test, paired t-test and Bonferroni correction) were assessed. Patients were divided into high- and low-risk groups depending on the OS and treatment response. The CNN segmentation and prediction utilized multimodality imaging data for a complementary in-depth risk analysis per patient. The following parameters correlated with longer OS: a TMTV < 50 mL; no metastases in the brain, bone, liver, spleen or pleura; ≤4 affected organ regions; no metastases; a Dmlesion > 37 mm or SULpeak < 1.3; a range of the ADCmean < 600 mm2/s. However, none of the parameters correlated significantly with the stratification of the patients into the high- or low-risk groups. For the CNN, the sensitivity, specificity, PPV and accuracy were 92%, 96%, 92% and 95%, respectively. Imaging biomarkers such as the metastatic involvement of specific organs, a high tumor burden, the presence of at least one large lesion or a high range of intermetastatic diffusivity were negative predictors for the OS, but the identification of high-risk patients was not feasible with the handcrafted parameters. In contrast, the proposed CNN supplied risk stratification with high specificity and sensitivity.

All-in-One Optofluidic Chip for Molecular Biosensing Assays.

Integrated biosensor platforms have become subjects of high interest for consolidated assay preparation and analysis to reduce sample-to-answer response times. By compactly combining as many biosensor processes and functions as possible into a single lab-on-chip device, all-in-one point-of-care devices can aid in the accessibility and speed of deployment due to their compact size and portability. Biomarker assay preparation and sensing are functionalities that are often carried out on separate devices, thus increasing opportunity of contamination, loss of sample volume, and other forms of error. Here, we demonstrate a complete lab-on-chip system combining sample preparation, on-chip optofluidic dye laser, and optical detection. We first show the integration of an on-chip distributed feedback dye laser for alignment-free optical excitation of particles moving through a fluidic channel. This capability is demonstrated by using Rhodamine 6G as the gain medium to excite single fluorescent microspheres at 575 nm. Next, we present an optofluidic PDMS platform combining a microvalve network (automaton) for sample preparation of nanoliter volumes, on-chip distributed feedback dye laser for target excitation, and optical detection. We conduct concurrent capture and fluorescence tagging of Zika virus nucleic acid on magnetic beads in 30 min. Target-carrying beads are then optically excited using the on-chip laser as they flow through an analysis channel, followed by highly specific fluorescence detection. This demonstration of a complete all-in-one biosensor is a tangible step in the development of a rapid, point-of-care device that can assist in limiting the severity of future outbreaks.

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.

Availability as key determinant in the palliative home care setting from the patients' and family caregivers' perspectives: A quantitative-qualitative-content analysis approach.

OBJECTIVE: A sense of security is important in palliative home care. Yet, knowledge about which components contribute most to feeling secure from the patients' and family caregivers' perspectives, especially since the introduction of specialist palliative home care, is sparse. The goal of the current study was to determine the key components contributing to a sense of security and how they relate to each other as experienced by patients and family caregivers in specialist and generalist palliative home care. METHODS: The current sub-study, as part of a larger study, was performed in different regions in Germany. Palliative care patients and family caregivers of at least 18 years of age, being cared for at home were interviewed using semi-structured interview guides following a three-factor model and analyzed by using a combined quantitative-qualitative-content approach. RESULTS: One hundred and ninty-seven patients and 10 carers completed interviews between December 2017 and April 2019. The majority of patients were diagnosed with an oncological disease. Sense of security was mentioned particularly often suggesting its high relevance. We identified nine subcategories that were all mentioned more frequently by specialist than generalist palliative home care recipients in the following order of priority and relation: (i) patient-centeredness: availability, provision of information/education, professional competence, patient empowerment, and trust (ii) organizational work: comprehensive responsibility, external collaboration, and internal cooperation, and (iii) direct communication. SIGNIFICANCE OF RESULTS: The work of specialist palliative home care services in particular was perceived as very effective and beneficial. Our findings confirm a previously developed three-factor model allowing for generalizability and revealed that availability was most important for improving the sense of security for effective palliative home care.

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.

[Smarter Medicine in Headache Care - presentation and discussion of 5 recommendations]. / Smarter Medicine in Diagnose und Behandlung von Kopfschmerzen.

Smarter Medicine in Headache Care - presentation and discussion of 5 recommendations Abstract. An unequivocal headache diagnosis cannot always be made. The lack of diagnostic tests able to prove primary headaches often prompts physicians to perform unnecessary examinations to reduce their uncertainty. When setting out the therapeutic strategy, again, insecurity often leads to mendable choices. In this Delphi study, members of the therapy commission of the Swiss Headache Society collected, rated, and re-rated doubtful and questionable procedures. Five recommendations that resulted from this survey are presented and reviewed in this article. The recommendations are: (A) no repeated cerebral imaging in headaches with unchanged phenotype; (B) no computed tomography in the work-up of non-acute headaches; (C) no tooth extraction to treat persistent idiopathic facial pain, (D) no migraine surgery; (E) no removal of amalgam fillings to treat headache disorders.

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.