Biology subjects

Barandun, G.

Publications and source records attributed to Barandun, G..

6 recordsLinked to original sources

bioRxiv2025

NFC-enabled Sensing Platform for the Onsite Determination of Asparagine in Food

Cooking foods rich in free asparagine (an amino acid that plays an important role in the synthesis of proteins), such as potatoes and flour-based products, can lead to the formation of acrylamide, a potent neurotoxin and potential carcinogen. Food manufacturers must quantify the levels of free asparagine before processing to minimize the formation of acrylamide, but conventional detection methods are often slow and expensive. We report a point-of-need measurement technology consisting of a chemically-functionalized paper-based electrical gas sensor and Near Field Communication (NFC)-enabled digital sensor interface (an integrated circuit) for rapid, cost-effective detection of free asparagine. Acid-functionalized paper-based electrical gas sensors selectively responds to ammonia gas, which is released during the enzymatic degradation of free asparagine. Through the use of the NFC-enabled digital sensor interface, a smartphone can wirelessly power and operate the paper-based gas sensor, enabling real-time quantification of free asparagine with a dedicated mobile application. We demonstrate a proof-of-concept sensor with a limit of detection of 3.19 {micro}g/mL, capable of detecting low levels of free asparagine in food products. This practical tool can facilitate better control over the levels of acrylamide in food and improve food safety.

bioengineering↗

bioRxiv2024

Enabling Packaging Integration of Paper-based Electrical Gas Sensors for the Monitoring of Spoilage in Fresh Spinach

Gas sensors present an alternative to traditional off-package food quality assessment, due to their high sensitivity and fast response without the need of sample pre-treatment. The safe integration of gas sensors into packaging without compromising sensitivity, response rate, and stability, however, remains a challenge. Such packaging integration of spoilage sensors is crucial towards preventing food waste and transitioning towards more sustainable supply chains. Here, we demonstrate a wide-ranging solution to enable the use of gas sensors for the continuous monitoring of food spoilage, building upon our previous work on Paper-based Electrical Gas Sensors (PEGS). By comparing various materials commonly used in the food industry, we analyze the optimal membrane to encapsulate PEGS for packaging integration. Focusing on spinach as a high-value crop, we assess the feasibility of PEGS to monitor the gases released during its spoilage at low and room temperatures. Finally, we integrate the sensors with wireless communication and batteryless electronics, creating a user-friendly system to evaluate the spoilage of spinach, operated by a smartphone via Near Field Communication (NFC). The work reported here provides an alternative approach that surpasses traditional on-site and in-line monitoring, ensuring comprehensive monitoring of food shelf life.

bioengineering↗

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↗

bioRxiv2023

Facilitating Electrochemical Lateral Flow Assay using NFC-Enabled Potentiostat and Nitrocellulose-based Metal Electrodes

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 used for the detection of Maize Mosaic Virus (MMV), a plant pathogen, as a proof-of-concept application.

bioengineering↗

bioRxiv2021

PEDOT:PSS-Modified Cotton Conductive Thread for Mass Manufacturing of Textile-Based Electrical Wearable Sensors by Computerized Embroidery

The textile industry has advanced processes that allow computerized manufacturing of garments at large volumes with precise visual patterns. The industry, however, is not able to mass fabricate clothes with seamlessly integrated wearable sensors, using its precise methods of fabrication (such as computerized embroidery). This is due to the lack of conductive threads compatible with standard manufacturing methods used in industry. In this work, we report a low-cost poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS)-modified cotton conductive thread (PECOTEX) that is compatible with computerized embroidery. The PECOTEX was produced using a crosslinking reaction between PEDOT:PSS and cotton thread using divinyl sulfone as the crosslinker. We extensively characterized and optimized our formulations to create a mechanically robust conductive thread that can be produced in large quantities in a roll-to-roll fashion. Using PECOTEX and a domestic computerized embroidery machine, we produced a series of wearable electrical sensors including a facemask for monitoring breathing, a t-shirt for monitoring heart activity and textile-based gas sensors for monitoring ammonia as technology demonstrators. PECOTEX has the potential to enable mass manufacturing of new classes of low-cost wearable sensors integrated into everyday clothes.

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↗