Microwave Spoof Surface Plasmon Polariton-Based Sensor for Ultrasensitive Detection of Liquid Analyte Dielectric Constant

In this paper, a microwave microfluidic sensor based on spoof surface plasmon polaritons (SSPPs) was proposed for ultrasensitive detection of dielectric constant. A novel unit cell for the SSPP structure is proposed and its behaviour and sensing potential analysed in detail. Based on the proposed cell, the SSPP microwave structure with a microfluidic reservoir is designed as a multilayer configuration to serve as a sensing platform for liquid analytes. The sensor is realized using a combination of rapid, cost-effective technologies of xurography, laser micromachining, and cold lamination bonding, and its potential is validated in the experiments with edible oil samples. The results demonstrate high sensitivity (850 MHz/epsilon unit) and excellent linearity (R2 = 0.9802) of the sensor, which, together with its low-cost and simple fabrication, make the proposed sensor an excellent candidate for the detection of small changes in the dielectric constant of edible oils and other liquid analytes

Mammalian Cell-Growth Monitoring Based on an Impedimetric Sensor and Image Processing within a Microfluidic Platform

In recent years, advancements in microfluidic and sensor technologies have led to the development of new methods for monitoring cell growth both in macro- and micro-systems. In this paper, a microfluidic (MF) platform with a microbioreactor and integrated impedimetric sensor is proposed for cell growth monitoring during the cell cultivation process in a scaled-down simulator. The impedimetric sensor with an interdigitated electrode (IDE) design was realized with inkjet printing and integrated into the custom-made MF platform, i.e., the scaled-down simulator. The proposed method, which was integrated into a simple and rapid fabrication MF system, presents an excellent candidate for the scaled-down analyses of cell growths that can be of use in, e.g., optimization of the cultivated meat bioprocess. When applied to MRC-5 cells as a model of adherent mammalian cells, the proposed sensor was able to precisely detect all phases of cell growth (the lag, exponential, stationary, and dying phases) during a 96-h cultivation period with limited available nutrients. By combining the impedimetric approach with image processing, the platform enables the real-time monitoring of biomasses and advanced control of cell growth progress in microbioreactors and scaled-down simulator systems

Artificial Neural Network Approach to Modelling of Metal Contents in Different Types of Chocolates

The relationships between the contents of various metals (Cu, Ni, Pb and Al) in different types of chocolates were studied using chemometric approach. Chemometric analysis was based on the application of artificial neural networks (ANN). ANN was performed in order to select the significant models for predicting the metal contents. ANN equations that represent the content of one metal as a function of the contents of other metals were established. The statistical quality of the generated mathematical models was determined by standard statistical measures and cross-validation parameters. High agreement between experimental and predicted values, obtained in the validation procedure, indicated the good quality of the models. The obtained results indicate the possibility of predicting the metal contents in different types of chocolate and define the strong non-linear relationship between metal contents

New Perspective on Comparative Chemometric and Molecular Modeling of Antifungal Activity and Herbicidal Potential of Alkyl and Cycloalkyl <i>s</i>-Triazine Derivatives

The contamination of the environment by pesticides is becoming a burning issue in many countries in the World. Development, design, and synthesis of new eco-friendly pesticides and modification of existing ones in order to improve their efficacy with the lowest impact on the environment are two main future possibilities in crop protection and the provision of sufficient food for the growing world population. The present study is focused on the comparative analysis of a series of eight symmetrical triazine derivatives, as potential herbicide candidates with acyclic (alkyl) and cyclic (cycloalkyl) substituents, in terms of their antifungal activity towards Aspergillus flavus as an opportunistic fungal pathogenic microorganism responsible for frequent contaminations of crops with aflatoxin, and in terms of their potential application as herbicides in maize, common wheat, barley, and rice crops. The applied methods include the chemometric pattern recognition method (hierarchical cluster analysis), experimental microbiological analysis of antifungal activity (agar well-diffusion method), and molecular docking of the triazines in the corresponding enzymes. The main findings of the conducted study indicate the significant antifungal activity of the studied triazine derivatives towards A. flavus, particularly the compounds with acyclic substituents; five out of eight studied triazines could be applied as systematic herbicides, while the other three triazines could be used as contact herbicides; the compounds with acyclic substituents could be more suitable for application for various crops protection than triazines with cyclic substituents

Low-cost goldleaf electrode as a platform for Escherichia coli immunodetection

&lt;p&gt;Gold electrodes are one of most prevalent substrates in electrochemical biosensors because they can be easily and highly efficiently functionalized with thiolated biomolecules. However, conventional methods to fabricate gold electrodes are costly, time-consuming and require onerous equipment. Here, an affordable method for rapid fabrication of an electrochemical immunosensor for Escherichia coli detection is presented. The gold electrode was generated using 24-karat gold leaves and lowcost polyvinyl chloride adhesive sheets covered with an insulating PTFE layer. The goldleaf electrode (GLE) was patterned using laser ablation and characterized by cyclic voltammetry, electrochemical impedance spectroscopy, scanning electronic microscopy, contact angle and 3D profiling. The GLEs were modified by a self-assembled mercaptopropionic monolayer, followed by surface activation to allow binding of the specific anti-E. coli antibody via carbodiimide linking. The biosensor showed a detection limit of 2 CFU/mL and a linear dynamic range of 10-10&lt;sup&gt;7&lt;/sup&gt;&nbsp;CFU/mL for E. coli cells. No false positive signals were obtained from control bacteria. The obtained results demonstrated suitability of GLE for use in biosensors with high reliability and reproducibility. It is foreseeable that our work will inspire design of point-of-need biosensors broadly applicable in low-resource settings.&lt;/p&gt