Plant-on-a-chip: continuous, soilless electrochemical monitoring of salt uptake and tolerance among different genotypes of tomato.

Tomatoes (Solanum lycopersicum), a high-value crop, exhibit a unique relationship with salt, where increased levels of NaCl can enhance flavor, aroma and nutritional quality but can cause oxidative damage and reduce yields. A drive for larger, better-looking tomatoes has reduced the importance of salt sensitivity, a concern considering that the sodium content of agricultural land is increasing over time. Currently, there are no simple ways of comparing salt tolerance between plants, where a holistic approach looking at [Na+] throughout the plant typically involves destructive, single time point measurements or expensive imaging techniques. Finding methods that collect rapid information in real time could improve the understanding of salt resistance in the field. Here we investigate the uptake of NaCl by tomatoes using TETRIS (Time-resolved Electrochemical Technology for plant Root environment In situ chemical Sensing), a platform used to measure chemical signals in the root area of living plants. Low-cost, screen-printed electrochemical sensors were used to measure changes in salt concentration via electrical impedance measurements, facilitating the monitoring of the uptake of ions by roots. We not only demonstrated differences in the rate of uptake of NaCl between tomato seedlings under different growth conditions, but also showed differences in uptake between varieties of tomato with different NaCl sensitivities and the relatively salt-resistant "wild tomato" (Solanum pimpinellifolium) sister species. Our results suggest that TETRIS could be used to ascertain physiological traits of salt resistance found in adult plants but at the seedling stage of growth. This extrapolation, and the possibility to multiplex and change sensor configuration, could enable high-throughput screening of many hundreds or thousands of mutants or varieties.

Parallel, Continuous Monitoring and Quantification of Programmed Cell Death in Plant Tissue.

Accurate quantification of hypersensitive response (HR) programmed cell death is imperative for understanding plant defense mechanisms and developing disease-resistant crop varieties. Here, a phenotyping platform for rapid, continuous-time, and quantitative assessment of HR is demonstrated: Parallel Automated Spectroscopy Tool for Electrolyte Leakage (PASTEL). Compared to traditional HR assays, PASTEL significantly improves temporal resolution and has high sensitivity, facilitating detection of microscopic levels of cell death. Validation is performed by transiently expressing the effector protein AVRblb2 in transgenic Nicotiana benthamiana (expressing the corresponding resistance protein Rpi-blb2) to reliably induce HR. Detection of cell death is achieved at microscopic intensities, where leaf tissue appears healthy to the naked eye one week after infiltration. PASTEL produces large amounts of frequency domain impedance data captured continuously. This data is used to develop supervised machine-learning (ML) models for classification of HR. Input data (inclusive of the entire tested concentration range) is classified as HR-positive or negative with 84.1% mean accuracy (F1 score = 0.75) at 1 h and with 87.8% mean accuracy (F1 score = 0.81) at 22 h. With PASTEL and the ML models produced in this work, it is possible to phenotype disease resistance in plants in hours instead of days to weeks.

NFC-enabled potentiostat and nitrocellulose-based metal electrodes for electrochemical lateral flow assay.

Rapid detection of pathogens at the point-of-need is crucial for preventing the spread of human, animal and plant diseases which can have devastating consequences both on the lives and livelihood of billions of people. Colorimetric, lateral flow assays consisting of a nitrocellulose membrane, are the preferred format today for low-cost on-site detection of pathogens. This assay format has, however, historically suffered from poor analytical performance and is not compatible with digital technologies. In this work, we report the development of a new class of digital diagnostics platform for precision point-of-need testing. This new versatile platform consists of two important innovations: i) A wireless and batteryless, microcontroller-based, low-cost Near Field Communication (NFC)-enabled potentiostat that brings high performance electroanalytical techniques (cyclic voltammetry, chronoamperometry, square wave voltammetry) to the field. The NFC-potentiostat can be operated with a mobile app by minimally trained users; ii) A new approach for producing nitrocellulose membranes with integrated electrodes that facilitate high performance electrochemical detection at the point-of-need. We produced an integrated system housed in a 3D-printed phone case and demonstrated its use for the detection of Maize Mosaic Virus (MMV), a plant pathogen, as a proof-of-concept application.

Ammonia detection: A pathway towards potential point-of-care diagnostics.

Invasive methods such as blood collection and biopsy are commonly used for testing liver and kidney function, which are painful, time-consuming, require trained personnel, and may not be easily accessible to people for their routine checkup. Early diagnosis of liver and kidney diseases can prevent severe symptoms and ensure better management of these patients. Emerging approaches such as breath and sweat analysis have shown potential as non-invasive methods for disease diagnosis. Among the many markers, ammonia is often used as a biomarker for the monitoring of liver and kidney functions. In this review we provide an insight into the production and expulsion of ammonia gas in the human body, the different diseases that could potentially use ammonia as biomarker and analytical devices such as chemiresistive gas sensors for non-invasive monitoring of this gas. The review also provides an understanding into the different materials, doping agents and substrates used to develop such multifunctional sensors. Finally, the current challenges and the possible future trends have been discussed.

Time-resolved chemical monitoring of whole plant roots with printed electrochemical sensors and machine learning.

Traditional single-point measurements fail to capture dynamic chemical responses of plants, which are complex, nonequilibrium biological systems. We report TETRIS (time-resolved electrochemical technology for plant root environment in situ chemical sensing), a real-time chemical phenotyping system for continuously monitoring chemical signals in the often-neglected plant root environment. TETRIS consisted of low-cost, highly scalable screen-printed electrochemical sensors for monitoring concentrations of salt, pH, and H2O2 in the root environment of whole plants, where multiplexing allowed for parallel sensing operation. TETRIS was used to measure ion uptake in tomato, kale, and rice and detected differences between nutrient and heavy metal ion uptake. Modulation of ion uptake with ion channel blocker LaCl3 was monitored by TETRIS and machine learning used to predict ion uptake. TETRIS has the potential to overcome the urgent "bottleneck" in high-throughput screening in producing high-yielding plant varieties with improved resistance against stress.

Continuous monitoring of chemical signals in plants under stress.

Time is an often-neglected variable in biological research. Plants respond to biotic and abiotic stressors with a range of chemical signals, but as plants are non-equilibrium systems, single-point measurements often cannot provide sufficient temporal resolution to capture these time-dependent signals. In this article, we critically review the advances in continuous monitoring of chemical signals in living plants under stress. We discuss methods for sustained measurement of the most important chemical species, including ions, organic molecules, inorganic molecules and radicals. We examine analytical and modelling approaches currently used to identify and predict stress in plants. We also explore how the methods discussed can be used for applications beyond a research laboratory, in agricultural settings. Finally, we present the current challenges and future perspectives for the continuous monitoring of chemical signals in plants.

Label-free electrochemical aptasensor for the detection of SARS-CoV-2 spike protein based on carbon cloth sputtered gold nanoparticles.

The proliferation and transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), or the (COVID-19) disease, has become a threat to worldwide biosecurity. Therefore, early diagnosis of COVID-19 is crucial to combat the ongoing infection spread. In this study we propose a flexible aptamer-based electrochemical sensor for the rapid, label-free detection of SARS-CoV-2 spike protein (SP). A platform made of a porous and flexible carbon cloth, coated with gold nanoparticles, to increase the conductivity and electrochemical performance of the material, was assembled with a thiol functionalized DNA aptamer via S-Au bonds, for the selective recognition of the SARS-CoV-2 SP. The various steps for the sensor preparation were followed by using scanning electron microscopy, cyclic voltammetry and differential pulse voltammetry (DPV). The proposed platform displayed good mechanical stability, revealing negligible changes on voltammetric responses to bending at various angles. Quantification of SARS-CoV-2 SP was performed by DPV and chronopotentiometry (CP), exploiting the changes of the electrical signals due the [Fe(CN)6]3-/4- redox probe, when SARS-CoV-2 SP binds to the aptamer immobilized on the electrode surface. Current density, in DPV, and square root of the transition time, in CP, varied linearly with the log[ SARS-CoV-2 SP], providing lower limits of detection (LOD) of 0.11 ng/mL and 37.8 ng/mL, respectively. The sensor displayed good selectivity, repeatability, and was tested in diluted human saliva, spiked with different SARS-CoV-2 SP concentrations, providing LODs of 0.167 ng/mL and 46.2 ng/mL for DPV and CP, respectively.

Challenges and Opportunities for Printed Electrical Gas Sensors.

Printed electrical gas sensors are a low-cost, lightweight, low-power, and potentially disposable alternative to gas sensors manufactured using conventional methods such as photolithography, etching, and chemical vapor deposition. The growing interest in Internet-of-Things, smart homes, wearable devices, and point-of-need sensors has been the main driver fueling the development of new classes of printed electrical gas sensors. In this Perspective, we provide an insight into the current research related to printed electrical gas sensors including materials, methods of fabrication, and applications in monitoring food quality, air quality, diagnosis of diseases, and detection of hazardous gases. We further describe the challenges and future opportunities for this emerging technology.

End-to-end design of wearable sensors.

Wearable devices provide an alternative pathway to clinical diagnostics by exploiting various physical, chemical and biological sensors to mine physiological (biophysical and/or biochemical) information in real time (preferably, continuously) and in a non-invasive or minimally invasive manner. These sensors can be worn in the form of glasses, jewellery, face masks, wristwatches, fitness bands, tattoo-like devices, bandages or other patches, and textiles. Wearables such as smartwatches have already proved their capability for the early detection and monitoring of the progression and treatment of various diseases, such as COVID-19 and Parkinson disease, through biophysical signals. Next-generation wearable sensors that enable the multimodal and/or multiplexed measurement of physical parameters and biochemical markers in real time and continuously could be a transformative technology for diagnostics, allowing for high-resolution and time-resolved historical recording of the health status of an individual. In this Review, we examine the building blocks of such wearable sensors, including the substrate materials, sensing mechanisms, power modules and decision-making units, by reflecting on the recent developments in the materials, engineering and data science of these components. Finally, we synthesize current trends in the field to provide predictions for the future trajectory of wearable sensors.

Bioinspired Stretchable Transducer for Wearable Continuous Monitoring of Respiratory Patterns in Humans and Animals.

A bio-inspired continuous wearable respiration sensor modeled after the lateral line system of fish is reported which is used for detecting mechanical disturbances in the water. Despite the clinical importance of monitoring respiratory activity in humans and animals, continuous measurements of breathing patterns and rates are rarely performed in or outside of clinics. This is largely because conventional sensors are too inconvenient or expensive for wearable sensing for most individuals and animals. The bio-inspired air-silicone composite transducer (ASiT) is placed on the chest and measures respiratory activity by continuously measuring the force applied to an air channel embedded inside a silicone-based elastomeric material. The force applied on the surface of the transducer during breathing changes the air pressure inside the channel, which is measured using a commercial pressure sensor and mixed-signal wireless electronics. The transducer produced in this work are extensively characterized and tested with humans, dogs, and laboratory rats. The bio-inspired ASiT may enable the early detection of a range of disorders that result in altered patterns of respiration. The technology reported can also be combined with artificial intelligence and cloud computing to algorithmically detect illness in humans and animals remotely, reducing unnecessary visits to clinics.

Multiplexed immunosensors for point-of-care diagnostic applications.

Accurate, reliable, and cost-effective immunosensors are clinically important for the early diagnosis and monitoring of progressive diseases, and multiplexed sensing is a promising strategy for the next generation of diagnostics. This strategy allows for the simultaneous detection and quantification of multiple biomarkers with significantly enhanced reproducibility and reliability, whilst requiring smaller sample volumes, fewer materials, and shorter average analysis time for individual biomarkers than individual tests. In this opinionated review, we compare different techniques for the development of multiplexed immunosensors. We review the state-of-the-art approaches in the field of multiplexed immunosensors using electrical, electrochemical, and optical methods. The barriers that prevent translating this sensing strategy into clinics are outlined together with the potential solutions. We also share our vision on how multiplexed immunosensors will continue their evolution in the coming years.

Sensors in blockchain.

Blockchain, the technology behind bitcoin, has stimulated global conversation around digital decentralization to connect societies and economies. Connected low-cost sensors within Internet of Things (IoT) networks may soon perform measurements, exchange data, and make decisions automatically over decentralized networks; these systems could improve healthcare, the quality of goods, and supply chain efficiency.

Self-powered ultrasensitive and highly stretchable temperature-strain sensing composite yarns.

With the emergence of stretchable/wearable devices, functions, such as sensing, energy storage/harvesting, and electrical conduction, should ideally be carried out by a single material, while retaining its ability to withstand large elastic deformations, to create compact, functionally-integrated and autonomous systems. A new class of trimodal, stretchable yarn-based transducer formed by coating commercially available Lycra® yarns with PEDOT:PSS is presented. The material developed can sense strain (first mode), and temperature (second mode) and can power itself thermoelectrically (third mode), eliminating the need for an external power-supply. The yarns were extensively characterized and obtained an ultrahigh (gauge factor ∼3.6 × 105, at 10-20% strain) and tunable (up to about 2 orders of magnitude) strain sensitivity together with a very high strain-at-break point (up to ∼1000%). These PEDOT:PSS-Lycra yarns also exhibited stable thermoelectric behavior (Seebeck coefficient of 15 µV K-1), which was exploited both for temperature sensing and self-powering (∼0.5 µW, for a 10-couple module at ΔT ∼ 95 K). The produced material has potential to be interfaced with microcontroller-based systems to create internet-enabled, internet-of-things type devices in a variety of form factors.

Low-Cost Optical Assays for Point-of-Care Diagnosis in Resource-Limited Settings.

Readily deployable, low-cost point-of-care medical devices such as lateral flow assays (LFAs), microfluidic paper-based analytical devices (µPADs), and microfluidic thread-based analytical devices (µTADs) are urgently needed in resource-poor settings. Governed by the ASSURED criteria (affordable, sensitive, specific, user-friendly, rapid and robust, equipment-free, and deliverability) set by the World Health Organization, these reliable platforms can screen a myriad of chemical and biological analytes including viruses, bacteria, proteins, electrolytes, and narcotics. The Ebola epidemic in 2014 and the ongoing pandemic of SARS-CoV-2 have exemplified the ever-increasing importance of timely diagnostics to limit the spread of diseases. This review provides a comprehensive survey of LFAs, µPADs, and µTADs that can be deployed in resource-limited settings. The subsequent commercialization of these technologies will benefit the public health, especially in areas where access to healthcare is limited.

The future of near-field communication-based wireless sensing.

Near-field communication emerged as a high-security, wireless, short-range, data exchange technology nearly two decades ago; its ability to simultaneously transfer power and data between devices offers exciting opportunities for the design of miniature, battery-free and disposable sensing systems in health care and food quality monitoring.

Point-of-use sensors and machine learning enable low-cost determination of soil nitrogen.

Overfertilization with nitrogen fertilizers has damaged the environment and health of soil, but standard laboratory testing of soil to determine the levels of nitrogen (mainly NH4+ and NO3-) is not performed regularly. Here we demonstrate that point-of-use measurements of NH4+, combined with soil conductivity, pH, easily accessible weather and timing data, allow instantaneous prediction of levels of NO3- in soil (R2 = 0.70) using a machine learning model. A long short-term memory recurrent neural network model can also be used to predict levels of NH4+ and NO3- up to 12 days into the future from a single measurement at day one, with [Formula: see text] and [Formula: see text], for unseen weather conditions. Our machine-learning-based approach eliminates the need for dedicated instruments to determine the levels of NO3- in soil. Nitrogenous soil nutrients can be determined and predicted with enough accuracy to forecast the impact of climate on fertilization planning and to tune timing for crop requirements, reducing overfertilization while improving crop yields.

Disposable silicon-based all-in-one micro-qPCR for rapid on-site detection of pathogens.

Rapid screening and low-cost diagnosis play a crucial role in choosing the correct course of intervention when dealing with highly infectious pathogens. This is especially important if the disease-causing agent has no effective treatment, such as the novel coronavirus SARS-CoV-2, and shows no or similar symptoms to other common infections. Here, we report a disposable silicon-based integrated Point-of-Need transducer (TriSilix) for real-time quantitative detection of pathogen-specific sequences of nucleic acids. TriSilix can be produced at wafer-scale in a standard laboratory (37 chips of 10 × 10 × 0.65 mm in size can be produced in 7 h, costing ~0.35 USD per device). We are able to quantitatively detect a 563 bp fragment of genomic DNA of Mycobacterium avium subspecies paratuberculosis through real-time PCR with a limit-of-detection of 20 fg, equivalent to a single bacterium, at the 35th cycle. Using TriSilix, we also detect the cDNA from SARS-CoV-2 (1 pg) with high specificity against SARS-CoV (2003).

Monolithic Solder-On Nanoporous Si-Cu Contacts for Stretchable Silicone Composite Sensors.

We report a method of creating solderable, mechanically robust, electrical contacts to interface (soft) silicone-based strain sensors with conventional (hard) solid-state electronics using a nanoporous Si-Cu composite. The Si-based solder-on electrical contact consists of a copper-plated nanoporous Si top surface formed through metal-assisted chemical etching and electroplating and a smooth Si bottom surface that can be covalently bonded onto silicone-based strain sensors through plasma bonding. We investigated the mechanical and electrical properties of the contacts proposed under relevant ranges of mechanical stress for applications in physiological monitoring and rehabilitation. We also produced a series of proof-of-concept devices, including a wearable respiration monitor, leg band for exercise monitoring, and squeeze ball for monitoring rehabilitation of patients with hand injuries or neurological disorders to demonstrate the mechanical robustness and versatility of the technology developed in real-world applications.