Passive Wireless Porous Biopolymer Sensors for At-Home Monitoring of Oil and Fatty Acid Nutrition.

Dietary oils─rich in omega-3, -6, and -9 fatty acids─exhibit critical impacts on health parameters such as cardiovascular function, bodily inflammation, and neurological development. There has emerged a need for low-cost, accessible method to assess dietary oil consumption and its health implications. Existing methods typically require specialized, complex equipment and extensive sample preparation steps, rendering them unsuitable for home use. Addressing this gap, herein, we study passive wireless, biocompatible biosensors that can be used to monitor dietary oils directly from foods either prepared or cooked in oil. This design uses broad-coupled split ring resonators interceded with porous silk fibroin biopolymer (requiring only food-safe materials, such as aluminum foil and biopolymer). These porous biopolymer films absorb oils at rates proportional to their viscosity/fatty acid composition and whose response can be measured wirelessly without any microelectronic components touching food. The engineering and mechanism of such sensors are explored, alongside their ability to measure the oil presence and fatty acid content directly from foods. Its simplicity, portability, and inexpensiveness are ideal for emerging needs in precision nutrition─such sensors may empower individuals to make informed dietary decisions based on direct-from-food measurements.

Amphibious epidermal area networks for uninterrupted wireless data and power transfer.

The human body exhibits complex, spatially distributed chemo-electro-mechanical processes that must be properly captured for emerging applications in virtual/augmented reality, precision health, activity monitoring, bionics, and more. A key factor in enabling such applications involves the seamless integration of multipurpose wearable sensors across the human body in different environments, spanning from indoor settings to outdoor landscapes. Here, we report a versatile epidermal body area network ecosystem that enables wireless power and data transmission to and from battery-free wearable sensors with continuous functionality from dry to underwater settings. This is achieved through an artificial near field propagation across the chain of biocompatible, magneto-inductive metamaterials in the form of stretchable waterborne skin patches-these are fully compatible with pre-existing consumer electronics. Our approach offers uninterrupted, self-powered communication for human status monitoring in harsh environments where traditional wireless solutions (such as Bluetooth, Wi-Fi or cellular) are unable to communicate reliably.

Feature Augmented Hybrid CNN for Stress Recognition Using Wrist-based Photoplethysmography Sensor.

Stress is a physiological state that hampers mental health and has serious consequences to physical health. More-over, the COVID-19 pandemic has increased stress levels among people across the globe. Therefore, continuous monitoring and detection of stress are necessary. The recent advances in wearable devices have allowed the monitoring of several physiological signals related to stress. Among them, wrist-worn wearable devices like smartwatches are most popular due to their convenient usage. And the photoplethysmography (PPG) sensor is the most prevalent sensor in almost all consumer-grade wrist-worn smartwatches. Therefore, this paper focuses on using a wrist-based PPG sensor that collects Blood Volume Pulse (BVP) signals to detect stress which may be applicable for consumer-grade wristwatches. Moreover, state-of-the-art works have used either classical machine learning algorithms to detect stress using hand-crafted features or have used deep learning algorithms like Convolutional Neural Network (CNN) which automatically extracts features. This paper proposes a novel hybrid CNN (H-CNN) classifier that uses both the hand-crafted features and the automatically extracted features by CNN to detect stress using the BVP signal. Evaluation on the benchmark WESAD dataset shows that, for 3-class classification (Baseline vs. Stress vs. Amusement), our proposed H-CNN outperforms traditional classifiers and normal CNN by ≈5% and ≈7% accuracy, and ≈10% and ≈7% macro F1 score, respectively. Also for 2-class classification (Stress vs. Non-stress), our proposed H-CNN outperforms traditional classifiers and normal CNN by ≈3% and ≈5% accuracy, and ≈3% and ≈7% macro F1score, respectively.

Feature Augmented Hybrid CNN for Stress Recognition Using Wrist-based Photoplethysmography Sensor.

Stress is a physiological state that hampers mental health and has serious consequences to physical health. Moreover, the COVID-19 pandemic has increased stress levels among people across the globe. Therefore, continuous monitoring and detection of stress are necessary. The recent advances in wearable devices have allowed the monitoring of several physiological signals related to stress. Among them, wrist-worn wearable devices like smartwatches are most popular due to their convenient usage. And the photoplethysmography (PPG) sensor is the most prevalent sensor in almost all consumer-grade wrist-worn smartwatches. Therefore, this paper focuses on using a wrist-based PPG sensor that collects Blood Volume Pulse (BVP) signals to detect stress which may be applicable for consumer-grade wristwatches. Moreover, state-of-the-art works have used either classical machine learning algorithms to detect stress using hand-crafted features or have used deep learning algorithms like Convolutional Neural Network (CNN) which automatically extracts features. This paper proposes a novel hybrid CNN (H-CNN) classifier that uses both the hand-crafted features and the automatically extracted features by CNN to detect stress using the BVP signal. Evaluation on the benchmark WESAD dataset shows that, for 3-class classification (Baseline vs. Stress vs. Amusement), our proposed H-CNN outperforms traditional classifiers and normal CNN by 5% and 7% accuracy, and 10% and 7% macro F1 score, respectively. Also for 2-class classification (Stress vs. Non-stress), our proposed H-CNN outperforms traditional classifiers and normal CNN by 3% and ~5% accuracy, and ~3% and ~7% macro F1 score, respectively.

Wireless Qi-powered, Multinodal and Multisensory Body Area Network for Mobile Health.

Wireless, battery-free Body Area Networks (BAN) enable reliable long-term health monitoring with minimal intervention, and have the potential to transform patient care via mobile health monitoring. Current approaches for achieving such battery-free networks are limited in the number, capability, and positioning of sensing nodes-this is related to constraints in power supply, data rate, and working distance requirements between the wireless power source and sensing nodes. Here, we investigate a Qi-based, near-field power transfer scheme that can effectively drive wireless, battery-free, multi-node and multi-sensor BAN over long distances. This consists of a single Qi power source (such as a cellphone), a detached/untethered Passive Intermediate Relay (PIR) (facilitates power transfer from a central Qi source to multiple nodes on the body), and finally individual/detached sensing nodes placed throughout the body. Alongside this power scheme we implement the star network topology of a Gazell protocol to enable the continuous connection of one host to many sensing nodes while minimizing data loss over long temporal periods. The high-power transmission capabilities of Qi enables wireless support for a multitude of sensors (up to 12), and sensing nodes (up to 6) with a single transmitter at long distances (60 cm) and a sample rate of 20 Hz. This scheme is studied both in-vitro and in-vivo on the body.

Passive and wireless, implantable glucose sensing with phenylboronic acid hydrogel-interlayer RF resonators.

A phenylboronic acid-based, hydrogel-interlayer Radio-Frequency (RF) resonator is demonstrated as a highly-responsive, passive and wireless sensor for glucose monitoring. Constructs are composed of unanchored, capacitively-coupled split rings interceded by glucose-responsive hydrogels. Phenylboronic acid-hydrogels exhibit volumetric and dielectric variations in response to environmental glucose concentrations-these are efficiently converted to large shifts in the resonant response of interlayer-RF sensors. These tiny, stretchable and scalable sensors (5 mm × 5 mm x 250 µm) require no microelectronics or power at the sensing node and can be read-out remotely via near-field coupling. Sensors exhibit high sensitivities (~10% shift in resonant frequency-corresponding to 50 MHz-per 150 mg/dL of glucose), possess a limit of detection of 10 mg/dL, and a step response time of approximately 1 h to abrupt shifts in carbohydrate concentration. Notably, these sensors exhibited no signal drift or hysteresis over the time periods characterized herein (45 days at room temperature). We transform sensors into bioelectronic RF reporter-tags via the attachment of a single LED-these remotely report on glucose concentration via emitted light. We anticipate the non-degradative, long-term nature of both RF read-out and phenylboronic acid-based hydrogels will enable biosensors capable of long-term, remote read-out of glucose.

Multi-Functional Hydrogel-Interlayer RF/NFC Resonators as a Versatile Platform for Passive and Wireless Biosensing.

Wearable sensors promise to transform human understanding of body state. However, despite many wearable sensor modalities that exist, few demonstrate the raw capabilities required for many emerging healthcare applications-passivity (and microelectronics-free), wireless readout, long-term operation, and specificity. Hydrogel-interlayer radio-frequency resonators are demonstrated as a versatile platform for passive and wireless biosensing. Fabricated using a simple vinyl cutter, the base resonator is composed of unanchored, broad-side coupled coils interceded by multifunctional hydrogels-such resonators are tuned to be sensitive to specific analytical or physical signals by modifying hydrogel composition. These resonators are transformed into near-field communication (NFC) sensor circuits through the simple attachment of an LED. These enable direct quantification of sensor state by cellphone and eye with no specialized electronics required. Resonator arrays are finally fused with silicone to form soft, wireless sensor skins that enable co-readout of analytical to physical signals while molded to human subjects. Such low-cost, accessible platforms can integrate with environments in transformative ways, enabling new applications in wireless sensing.

Programmable Hydrogel Ionic Circuits for Biologically Matched Electronic Interfaces.

The increased need for wearable and implantable medical devices has driven the demand for electronics that interface with living systems. Current bioelectronic systems have not fully resolved mismatches between engineered circuits and biological systems, including the resulting pain and damage to biological tissues. Here, salt/poly(ethylene glycol) (PEG) aqueous two-phase systems are utilized to generate programmable hydrogel ionic circuits. High-conductivity salt-solution patterns are stably encapsulated within PEG hydrogel matrices using salt/PEG phase separation, which route ionic current with high resolution and enable localized delivery of electrical stimulation. This strategy allows designer electronics that match biological systems, including transparency, stretchability, complete aqueous-based connective interface, distribution of ionic electrical signals between engineered and biological systems, and avoidance of tissue damage from electrical stimulation. The potential of such systems is demonstrated by generating light-emitting diode (LED)-based displays, skin-mounted electronics, and stimulators that deliver localized current to in vitro neuron cultures and muscles in vivo with reduced adverse effects. Such electronic platforms may form the basis of future biointegrated electronic systems.

Functional, RF-Trilayer Sensors for Tooth-Mounted, Wireless Monitoring of the Oral Cavity and Food Consumption.

Wearable devices have emerged as powerful tools for personalized healthcare in spite of some challenges that limit their widespread applicability as continuous monitors of physiological information. Here, a materials-based strategy to add utility to traditional dielectric sensors by developing a conformal radiofrequency (RF) construct composed of an active layer encapsulated between two reverse-facing split ring resonators is applied. These small (down to 2 mm × 2 mm) passive dielectric sensors possess enhanced sensitivity and can be further augmented by functionalization of this interlayer material. Demonstrator devices are shown where the interlayer is: (i) a porous silk film, and (ii) a modified PNIPAM hydrogel that swells with pH or temperature. In vivo use is demonstrated by adhesion of the device on tooth enamel to detect foods during human ingestion. Such sensors can be easily multiplexed and yield data-rich temporal information during the diffusion of analytes within the trilayer structure. This format could be extended to a suite of interlayer materials for sensing devices of added use and specificity.

Elastomeric sensor surfaces for high-throughput single-cell force cytometry.

As cells with aberrant force-generating phenotypes can directly lead to disease, cellular force-generation mechanisms are high-value targets for new therapies. Here, we show that single-cell force sensors embedded in elastomers enable single-cell force measurements with ~100-fold improvement in throughput than was previously possible. The microtechnology is scalable and seamlessly integrates with the multi-well plate format, enabling highly parallelized time-course studies. In this regard, we show that airway smooth muscle cells isolated from fatally asthmatic patients have innately greater and faster force-generation capacity in response to stimulation than healthy control cells. By simultaneously tracing agonist-induced calcium flux and contractility in the same cell, we show that the calcium level is ultimately a poor quantitative predictor of cellular force generation. Finally, by quantifying phagocytic forces in thousands of individual human macrophages, we show that force initiation is a digital response (rather than a proportional one) to the proper immunogen. By combining mechanobiology at the single-cell level with high-throughput capabilities, this microtechnology can support drug-discovery efforts for clinical conditions associated with aberrant cellular force generation.

Publisher Correction: Elastomeric sensor surfaces for high-throughput single-cell force cytometry.

In the version of this Article originally published, in Fig. 1a, all cells in the top schematic were missing, and in the bottom-left schematic showing multiple pattern shapes, two cells were missing in the bottom-right corner. This figure has now been updated in all versions of the Article.

Modulation of Multiscale 3D Lattices through Conformational Control: Painting Silk Inverse Opals with Water and Light.

Structural proteins from naturally occurring materials are an inspiring template for material design and synthesis at multiple scales. The ability to control the assembly and conformation of such materials offers the opportunity to define fabrication approaches that recapitulate the dimensional hierarchy and structure-function relationships found in nature. A simple and versatile directed assembly method of silk fibroin, which allows the design of structures across multiple dimensional scales by generating and tuning structural color in large-scale, macro defect-free colloidally assembled 3D nanostructures in the form of silk inverse opals (SIOs) is reported. This approach effectively combines bottom-up and top-down techniques to obtain control on the nanoscale (through silk conformational changes), microscale (through patterning), and macroscale (through colloidal assembly), ultimately resulting in a controllable photonic lattice with predefined spectral behavior, with a resulting palette spanning almost the entire visible range. As a demonstration of the approach, examples of "multispectral" SIOs, paired with theoretical calculations and analysis of their response as a function of changes of lattice constants and refractive index contrast are illustrated.

Directed assembly of bio-inspired hierarchical materials with controlled nanofibrillar architectures.

In natural systems, directed self-assembly of structural proteins produces complex, hierarchical materials that exhibit a unique combination of mechanical, chemical and transport properties. This controlled process covers dimensions ranging from the nano- to the macroscale. Such materials are desirable to synthesize integrated and adaptive materials and systems. We describe a bio-inspired process to generate hierarchically defined structures with multiscale morphology by using regenerated silk fibroin. The combination of protein self-assembly and microscale mechanical constraints is used to form oriented, porous nanofibrillar networks within predesigned macroscopic structures. This approach allows us to predefine the mechanical and physical properties of these materials, achieved by the definition of gradients in nano- to macroscale order. We fabricate centimetre-scale material geometries including anchors, cables, lattices and webs, as well as functional materials with structure-dependent strength and anisotropic thermal transport. Finally, multiple three-dimensional geometries and doped nanofibrillar constructs are presented to illustrate the facile integration of synthetic and natural additives to form functional, interactive, hierarchical networks.

Evaluation of Silk Inverse Opals for "Smart" Tissue Culture.

Visually tracking the subtle aspects of biological systems in real time during tissue culture remains challenging. Herein, we demonstrate the use of bioactive, cytocompatible, and biodegradable inverse opals from silk as a multifunctional substrate to transduce both the optical information and cells during tissue culture. We show that these substrates can visually track substrate degradation in various proteases during tissue digestion and protein deposition during the growth of mesenchymal stem cells. Uniquely, these substrates can be integrated in multiple steps of tissue culture for simple-to-use, visual, and quantitative detectors of bioactivity. These substrates can also be doped, demonstrated here with gold nanoparticles, to allow additional control of cell functions.

High-throughput physical phenotyping of cell differentiation.

In this report, we present multiparameter deformability cytometry (m-DC), in which we explore a large set of parameters describing the physical phenotypes of pluripotent cells and their derivatives. m-DC utilizes microfluidic inertial focusing and hydrodynamic stretching of single cells in conjunction with high-speed video recording to realize high-throughput characterization of over 20 different cell motion and morphology-derived parameters. Parameters extracted from videos include size, deformability, deformation kinetics, and morphology. We train support vector machines that provide evidence that these additional physical measurements improve classification of induced pluripotent stem cells, mesenchymal stem cells, neural stem cells, and their derivatives compared to size and deformability alone. In addition, we utilize visual interactive stochastic neighbor embedding to visually map the high-dimensional physical phenotypic spaces occupied by these stem cells and their progeny and the pathways traversed during differentiation. This report demonstrates the potential of m-DC for improving understanding of physical differences that arise as cells differentiate and identifying cell subpopulations in a label-free manner. Ultimately, such approaches could broaden our understanding of subtle changes in cell phenotypes and their roles in human biology.

Multiparameter mechanical and morphometric screening of cells.

We introduce a label-free method to rapidly phenotype and classify cells purely based on physical properties. We extract 15 biophysical parameters from cells as they deform in a microfluidic stretching flow field via high-speed microscopy and apply machine-learning approaches to discriminate different cell types and states. When employing the full 15 dimensional dataset, the technique robustly classifies individual cells based on their pluripotency, with accuracy above 95%. Rheological and morphological properties of cells while deforming were critical for this classification. We also show the application of this method in accurate classifying cells based on their viability, drug screening and detecting populations of malignant cells in mixed samples. We show that some of the extracted parameters are not linearly independent, and in fact we reach maximum classification accuracy by using only a subset of parameters. However, the informative subsets could vary depending on cell types in the sample. This work shows the utility of an assay purely based on intrinsic biophysical properties of cells to identify changes in cell state. In addition to a label-free alternative to flow cytometry in certain applications, this work, also can provide novel intracellular metrics that would not be feasible with labeled approaches (i.e. flow cytometry).

Bio-functionalized silk hydrogel microfluidic systems.

Bio-functionalized microfluidic systems were developed based on a silk protein hydrogel elastomeric materials. A facile multilayer fabrication method using gelatin sacrificial molding and layer-by-layer assembly was implemented to construct interconnected, three dimensional (3D) microchannel networks in silk hydrogels at 100 µm minimum feature resolution. Mechanically activated valves were implemented to demonstrate pneumatic control of microflow. The silk hydrogel microfluidics exhibit controllable mechanical properties, long-term stability in various environmental conditions, tunable in vitro and in vivo degradability in addition to optical transparency, providing unique features for cell/tissue-related applications than conventional polydimethylsiloxane (PDMS) and existing hydrogel-based microfluidic options. As demonstrated in the work here, the all aqueous-based fabrication process at ambient conditions enabled the incorporation of active biological substances in the bulk phase of these new silk microfluidic systems during device fabrication, including enzymes and living cells, which are able to interact with the fluid flow in the microchannels. These silk hydrogel-based microfluidic systems offer new opportunities in engineering active diagnostic devices, tissues and organs that could be integrated in vivo, and for on-chip cell sensing systems.

Quantitative Magnetic Separation of Particles and Cells Using Gradient Magnetic Ratcheting.

Extraction of rare target cells from biosamples is enabling for life science research. Traditional rare cell separation techniques, such as magnetic activated cell sorting, are robust but perform coarse, qualitative separations based on surface antigen expression. A quantitative magnetic separation technology is reported using high-force magnetic ratcheting over arrays of magnetically soft micropillars with gradient spacing, and the system is used to separate and concentrate magnetic beads based on iron oxide content (IOC) and cells based on surface expression. The system consists of a microchip of permalloy micropillar arrays with increasing lateral pitch and a mechatronic device to generate a cycling magnetic field. Particles with higher IOC separate and equilibrate along the miropillar array at larger pitches. A semi-analytical model is developed that predicts behavior for particles and cells. Using the system, LNCaP cells are separated based on the bound quantity of 1 µm anti-epithelial cell adhesion molecule (EpCAM) particles as a metric for expression. The ratcheting cytometry system is able to resolve a ±13 bound particle differential, successfully distinguishing LNCaP from PC3 populations based on EpCAM expression, correlating with flow cytometry analysis. As a proof-of-concept, EpCAM-labeled cells from patient blood are isolated with 74% purity, demonstrating potential toward a quantitative magnetic separation instrument.

Direct Gradient Photolithography of Photodegradable Hydrogels with Patterned Stiffness Control with Submicrometer Resolution.

Cell response to matrix mechanics is well-known; however, the ability to spatially pattern matrix stiffness to a high degree of control has been difficult to attain. This study describes the use of maskless photolithography as a flexible process for direct, noncontact gradient patterning of photodegradable hydrogels with custom graphics. Any input gray scale image can be used to directly chart hydrogel cross-link density as a function of spatial position. Hydrogels can be patterned with submicron resolution, with length scales within a single substrate spanning several orders of magnitude. A quantitative relationship between input grayscale image pixel intensity and output gel stiffness is validated, allowing for direct gradient patterning. Such physical gradient hydrogel constructs are rapidly produced in a highly controlled fashion with measured stiffness ranges and length scales that are physiologically relevant. Mesenchymal stem cells cultured on these physical gradients matrices congregate and align orthogonal to the gradient direction along iso-degraded lines. This approach results in a robust and high-throughput platform to answer key questions about cell response in heterogeneous physical environments.

Engineering cortical neuron polarity with nanomagnets on a chip.

Intra- and extracellular signaling play critical roles in cell polarity, ultimately leading to the development of functional cell-cell connections, tissues, and organs. In the brain, pathologically oriented neurons are often the cause for disordered circuits, severely impacting motor function, perception, and memory. Aside from control through gene expression and signaling pathways, it is known that nervous system development can be manipulated by mechanical stimuli (e.g., outgrowth of axons through externally applied forces). The inverse is true as well: intracellular molecular signals can be converted into forces to yield axonal outgrowth. The complete role played by mechanical signals in mediating single-cell polarity, however, remains currently unclear. Here we employ highly parallelized nanomagnets on a chip to exert local mechanical stimuli on cortical neurons, independently of the amount of superparamagnetic nanoparticles taken up by the cells. The chip-based approach was utilized to quantify the effect of nanoparticle-mediated forces on the intracellular cytoskeleton as visualized by the distribution of the microtubule-associated protein tau. While single cortical neurons prefer to assemble tau proteins following poly-L-lysine surface cues, an optimal force range of 4.5-70 pN by the nanomagnets initiated a tau distribution opposed to the pattern cue. In larger cell clusters (groups comprising six or more cells), nanoparticle-mediated forces induced tau repositioning in an observed range of 190-270 pN, and initiation of magnetic field-directed cell displacement was observed at forces above 300 pN. Our findings lay the groundwork for high-resolution mechanical encoding of neural networks in vitro, mechanically driven cell polarization in brain tissues, and neurotherapeutic approaches using functionalized superparamagnetic nanoparticles to potentially restore disordered neural circuits.