Biology subjects

Kasimatis, M.

Publications and source records attributed to Kasimatis, M..

5 recordsLinked to original sources

bioRxiv2024

Wearable facemask-attached disposable printed sensor arrays for point-of-need monitoring of ammonia in breath

Blood sampling, despite its historical significance in clinical diagnostics, poses challenges such as invasiveness, infection risks, and limited temporal fidelity for continuous monitoring. In contrast, exhaled breath offers a non-invasive, pain-free, and continuous sampling method, carrying biochemical information through volatile compounds like ammonia (NH3). NH3 in exhaled breath, influenced by kidney function, emerges as a promising biomarker for renal health assessment, particularly in resource-limited settings lacking extensive healthcare infrastructure. Current analytical methods for breath ammonia, though effective, often face practical limitations. In this work, we introduce a low-cost, internet-connected, paper-based wearable device for measuring exhaled ammonia, designed for early detection of kidney dysfunction at the point-of-need. The device, which attaches to disposable facemasks, utilizes a disposable paper-based sensor array housed in a biodegradable plastic enclosure to mitigate high relative humidity (RH) issues in breath analysis. We validated our technology using a laboratory setup and human subjects who consumed ammonium chloride-containing candy to simulate elevated breath ammonia. Our wearable sensor offers a promising solution for rapid, point-of-need kidney dysfunction screening, particularly valuable in resource-limited settings. This approach has potential applications beyond kidney health monitoring, including chemical industry safety and environmental sensing, paving the way for accessible, continuous health monitoring.

bioengineering↗

bioRxiv2022

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

We report a bio-inspired continuous wearable respiration sensor modeled after the lateral line system of fish which is used by the fish 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 due to conventional sensors being too inconvenient or expensive for wearable sensing for most individuals and animals. The bio-inspired air-silicone composite transducer 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. We extensively characterized the transducer produced in this work and tested it with humans, dogs, and laboratory rats. The bio-inspired air-silicone composite transducer 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.

bioengineering↗

bioRxiv2020

Determining and Predicting Soil Chemistry with a Point-of-Use Sensor Toolkit and Machine Learning Model

Overfertilization with nitrogen fertilizers has damaged the environment and health of soil; yields are declining, while the population continues to rise. Soil is a complex, living organism which is constantly evolving, physically, chemically and biologically. Standard laboratory testing of soil to determine the levels of nitrogen (mainly NH4+ and NO3-) is infrequent as it is expensive and slow and levels of nitrogen vary on short timescales. Current testing practices, therefore, are not useful to guide fertilization. We demonstrate that Point-of-Use (PoU) measurements of NH4+, when combined with soil conductivity, pH, easily accessible weather (in this study, we simulated weather in the laboratory) and timing data (i.e. days passed since fertilization), allow instantaneous prediction of levels of NO3- in soil with of R2=0.70 using a machine learning (ML) model (the use of higher-precision laboratory measurements instead of PoU measurements increase R2 to 0.87 for the same model). We also show that a long short-term memory recurrent neural network model can be used to predict levels of NH4+ and NO3- up to 12 days into the future from a single measurement at day one, with R2NH4+ = 0.64 and R2NO3- = 0.70, for unseen weather conditions. To measure NH4+ in soil at the PoU easily and inexpensively, we also developed a new sensor that uses chemically functionalized near zero-cost paper-based electrical gas sensors. This new technology can detect the concentration of NH4+ in soil down to 3{+/-}1ppm (R2=0.85). Gas-phase sensing provides a robust method of sensing NH4+ due to the reduced complexity of the gas-phase sample. Our machine learning-based approach eliminates the need of using dedicated, expensive sensing instruments to determine the levels of NO3- in soil which is difficult to measure reliably with inexpensive technologies; furthermore, crucial nitrogenous soil nutrients can be determined and predicted with enough accuracy to forecast the impact of climate on fertilization planning, and tune timing for crop requirements, reducing overfertilization while improving crop yields.

bioengineering↗

bioRxiv2020

Ultra-Low-Cost Integrated Silicon-based Transducer for On-Site, Genetic Detection of Pathogens

Rapid screening and low-cost diagnosis play a crucial role in choosing the correct course of intervention e.g., drug therapy, quarantine, no action etc. 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 (the pathogen causing COVID-19), and shows no or similar symptoms to other common infections. We report a silicon-based integrated Point-of-Need (PoN) transducer (TriSilix) that can chemically-amplify and detect pathogen-specific sequences of nucleic acids (NA) quantitatively in real-time. Unlike other silicon-based technologies, TriSilix can be produced at wafer-scale in a standard laboratory; we have developed a series of methodologies based on metal-assisted chemical (wet) etching, electroplating, thermal bonding and laser-cutting to enable a cleanroom-free low-cost fabrication that does not require processing in an advanced semiconductor foundry. TriSilix is, therefore, resilient to disruptions in the global supply chain as the devices can be produced anywhere in the world. To create an ultra-low-cost device, the architecture proposed exploits the intrinsic properties of silicon and integrates three modes of operation in a single chip: i) electrical (Joule) heater, ii) temperature sensor (i.e. thermistor) with a negative temperature coefficient that can provide the precise temperature of the sample solution during reaction and iii) electrochemical sensor for detecting target NA. Using TriSilix, the sample solution can be maintained at a single, specific temperature (needed for isothermal amplification of NA such as Recombinase Polymerase Amplification (RPA) or cycled between different temperatures (with a precision of {+/-}1.3{degrees}C) for Polymerase Chain Reaction (PCR) while the exact concentration of amplicons is measured quantitatively and in real-time electrochemically. A single 4-inch Si wafer yields 37 TriSilix chips of 10x10x0.65 mm in size and can be produced in 7 hours, costing ~US $0.35 per device. The system is operated digitally, portable and low power - capable of running up to 35 tests with a 4000 mAh battery (a typical battery capacity of a modern smartphone). We were able to quantitatively detect a 563-bp fragment (Insertion Sequence IS900) of the genomic DNA of M. avium subsp. paratuberculosis (extracted from cultured field samples) through PCR in real-time with a Limit-of-Detection of 20 fg, equivalent to a single bacterium, at the 30th cycle. Using TriSilix, we also detected the cDNA from SARS-CoV-2 (1 pg), through PCR, with high specificity against SARS-CoV (2003).

bioengineering↗

bioRxiv2019

Stretchable Composite Acoustic Transducer for Wearable Monitoring of Vital Signs

We report a highly flexible, stretchable, and mechanically robust low-cost soft composite consisting of silicone polymers and water (or hydrogels). When combined with conventional acoustic transducers, the materials reported enable high performance real-time monitoring of heart and respiratory patterns over layers of clothing (or furry skin of animals) without the need for direct contact with the skin. Our approach enables an entirely new method of fabrication that involves encapsulation of water and hydrogels with silicones and exploits the ability of sound waves to travel through the body. The system proposed outperforms commercial, metal-based stethoscopes for the auscultation of the heart when worn over clothing and is less susceptible to motion artefacts. We have tested the system both with human and furry animal subjects (i.e. dogs), primarily focusing on monitoring the heart, however, we also present initial results on monitoring breathing. Our work is especially important because it is the first demonstration of a stretchable sensor that is suitable for use with furry animals and do not require shaving of the animal for data acquisition.

bioengineering↗