Universal Method Based on Layer-by-Layer Assembly for Aptamer-Based Sensors for Small-Molecule Detection.

Development of a fast and accurate pesticide analysis system is a challenging task, as a large amount of commonly used pesticide has negative effects on humans' health. Detection of pesticide residues is crucial for food safety management and environmental protection. Aptamers─short single-stranded oligonucleotides (RNA or DNA) selected by aptamer selection method SELEX─can selectively bind to their target pesticide molecules with high affinity. Thus, in the present study, we developed an electrochemical biosensor based on aptamers to detect the commonly used pesticide, glyphosate. Carbon fibers were used as the platform to assemble polyelectrolyte layers with the incorporated aptamers selectively binding with glyphosate molecules for electrochemical detection. The best limit of detection of 0.3 µM was achieved at open-circuit potential measurements, which is comparable to the current need in detection of glyphosate. The developed method can be implemented into existing systems for the determination of pesticides on farms to control residual concentrations of glyphosate in soil and water.

Electrochemical Sensor to Detect Antibiotics in Milk Based on Machine Learning Algorithms.

The present study is dedicated to the problem of electrochemical analysis of multicomponent mixtures, such as milk. A combination of cyclic voltammetry facilities and machine learning techniques made it possible to create a pattern recognition system for the detection of antibiotic residues in skimmed milk. A multielectrode sensor including copper, nickel, and carbon fiber was fabricated for the collection of electrochemical data. Processes occurring at the electrode surface were discussed and simulated with the help of molecular docking and density functional theory modeling. It was assumed that the antibiotic fingerprint reveals a potential drift of electrodes, owing to complexation with metal ions present in milk. The gradient boosting algorithm showed the best efficiency in training the machine learning model. High accuracy was achieved for the recognition of antibiotics in milk. The elaborated method may be incorporated into existing milking systems at dairy farms for monitoring the residue concentrations of antibiotics.

Soft Hydrogel Actuator for Fast Machine-Learning-Assisted Bacteria Detection.

We demonstrate that our bio-electrochemical platform facilitates the reduction of detection time from the 3-day period of the existing tests to 15 min. Machine learning and robotized bioanalytical platforms require the principles such as hydrogel-based actuators for fast and easy analysis of bioactive analytes. Bacteria are fragile and environmentally sensitive microorganisms that require a special environment to support their lifecycles during analytical tests. Here, we develop a bio-electrochemical platform based on the soft hydrogel/eutectic gallium-indium alloy interface for the detection of Streptococcus thermophilus and Bacillus coagulans bacteria in various mediums. The soft hydrogel-based device is capable to support bacteria' viability during detection time. Current-voltage data are used for multilayer perceptron algorithm training. The multilayer perceptron model is capable of detecting bacterial concentrations in the 104 to 108 cfu/mL range of the culture medium or in the dairy products with high accuracy (94%). Such a fast and easy biodetection is extremely important for food and agriculture industries and biomedical and environmental science.

Silver melamine thin film as a flexible platform for SERS analysis.

New SERS detection platforms are required for the quick and easy preparation of sensing devices for food, agriculture, and environmental science. For quantitative sensing, it is important that a sensing material, in addition to efficient sensing, provides extraction and concentration of the target molecules such as toxic pesticides or healthy vitamins. We design such films adopting the Liesegang rings formation process that includes the reaction-diffusion of silver nitrate and melamine followed by the precipitation of different intermediates and their reduction by light in a pectin medium. Surprisingly, we find that the presence of melamine provides an excellent substrate for the extraction of pollutants at the solid-liquid interface giving rise to a powerful but easy and fast method for the quantification of fruits' quality. The complex silver and melamine containing films show high sensitivity even at relatively low silver concentrations.

ElectroSens Platform with a Polyelectrolyte-Based Carbon Fiber Sensor for Point-of-Care Analysis of Zn in Blood and Urine.

In this paper, we describe an electrochemical sensing platform-ElectroSens-for the detection of Zn based on self-assembled polyelectrolyte multilayers on the carbon fiber (CF) electrode surface. The CF-extended surface facilitates the usage of a small volume electrochemical cell (1 mL) without stirring. This approach allows making a low-cost three-electrode platform. Working electrode modification with layer-by-layer assembly of polyethyleneimine (PEI), poly(sodium 4-styrenesulfonate) (PSS), and mercury nitrate layers eliminates solution toxicity and provides stable stripping voltammetry measurements. The stable, robust, sustainable, and even reusable Ag/AgCl reference electrode consists of adsorbed 32 PEI-KCl/PSS-KCl bilayers on the CF/silver paste separated from the outer solution by a polyvinyl chloride membrane. The polyelectrolyte-based sensor interface prevents adsorption of protein molecules from biological liquids on the CF surface that leads to a sensitivity increase of up to 2.2 µA/M for Zn2+ detection and provides a low limit of detection of 4.6 × 10-8 M. The linear range for Zn detection is 1 × 10-7 to 1 × 10-5 M. A portable potentiostat connected via wireless to a smartphone with an android-based software is also provided. The ElectroSens demonstrates reproducibility and repeatability of data for the detection of Zn in blood and urine without the digestion step.

Ultrasound-assisted fabrication of gluten-free dough for automatic producing dumplings.

Nowadays celiac disease is becoming more common. It is the autonomic genetic disease that is accompanied by damage to the intestines due to a reaction to eating some proteins. People who are suffering from celiac disease cannot eat food containing gluten, including dough made from gluten-containing seeds. But the gluten-free dough has commonly bad rheological properties and cannot be used for automatic molding the dumplings. In this article, we propose the ultrasonic-assisted technology to fabricate the gluten-free dough with improved rheological properties acceptable for automatic molding of the dumplings. Application of ultrasonic treatment at a frequency of 35 kHz during the dough preparation leads to the homogenization of the dough structure and changing the rheological properties of the dough. The ultrasound induces mechanical, physical and chemical/biochemical changes of the dough components through cavitation. The sonication causes a doubled dough volume increase followed by an additional mass yield of the dumplings equal 2-10% per kilogram of dough. Besides extra beneficial economic effect, our technology provides an additional sterilization effect of the fabricated dough.

Thin and Flexible Ion Sensors Based on Polyelectrolyte Multilayers Assembled onto the Carbon Adhesive Tape.

A novel flexible ion-selective sensor for potassium and sodium detection was proposed. Flexible ion-selective electrodes with pseudo-liquid internal solution on contrary to the system with a solid contact provided a more stable analytical signal. Such advantages were achieved because of polyelectrolyte (PEI/PSS) layers adsorption on the conduct substrate with a layer-by-layer technique. Such an approach demonstrated that ion-selective electrodes save sensitivity with Nernstian dependence: 56.2 ± 1.4 mV/dec a Na+ and 56.3 ± 1.9 mV/dec a K+ , as well as a fast time of response for potassium (5 s) and sodium (8 s) was shown. The sensing platform proposed demonstrates a better time of response and is close to the Nernstian value of sensitivity with a sensor low cost. The results proposed confirm a pseudo-liquid junction for the ion-selective electrode. Biocompatibility of an ion-selective sensing platform was demonstrated at potassium potentiometric measurements in Escherichia coli biofilms. Potassium levels in a biofilm were measured with potentiometry and showed agreement with the previous results.