In this work, we extended our previous studies on the limitations of classical contact models from polymers to a biological system. We used yeast as a model system to investigate how contact evolution during indentation affects the accuracy of AFM-based determination of Young's modulus. We proposed a practical correction framework for the classical Hertz and Sneddon flat-punch models to improve the extraction of mechanical properties from experimental data. Force-indentation curves were measured using a spherical (SPHERE) probe with a 2 μm radius and a flat (FLAT) probe with a 4 μm radius of plateau. The experimental results were analyzed using both corrected and uncorrected contact models, while a finite element analysis (FEA) model was used to determine the contact radius-indentation dependence. It showed that Young's modulus estimated from AFM indentation using classical formulations is probe-dependent because the contact radius is inadequately described. By incorporating the FEA-derived effective contact radius into Hertz and Sneddon contact models, the same Young's modulus was obtained for yeast with both probes and compared to reference values with other techniques. These findings establish contact evolution as a governing factor in AFM-based cell mechanics and provide a practical route toward robust, probe-independent, and more accurate determination of mechanical properties for living cells.

Biofuel cells (BFCs) generate electricity by converting chemical energy into electrical energy using biological systems. Saccharomyces cerevisiae (yeast) is an attractive biocatalyst for BFCs due to its robustness, low cost, and metabolic versatility; however, electron transfer from the intracellular reactions to the electrode is limited by the cell membrane. Nystatin is an antifungal antibiotic that increases the permeability of fungal membranes. We hypothesized that sub-lethal nystatin treatment could enhance mediator-assisted electron transfer without compromising cell viability. In this work, yeast was treated with nystatin during cultivation at concentrations of up to 6 µg/mL and combined with a dual-mediator system consisting of a lipophilic mediator (9,10-phenanthrenequinone, PQ) and a hydrophilic mediator (potassium ferricyanide). Scanning electrochemical microscopy revealed that the dual-mediator system increased local current responses by approximately fivefold compared to a single mediator (from ~11 pA to ~59 pA), and that nystatin-treated yeast exhibited higher local electrochemical activity than untreated yeast (maximum currents of ~0.476 nA versus ~0.303 nA). Microbial fuel cell measurements showed that nystatin treatment increased the maximum power density from approximately 0.58 mW/m2 to approximately 0.62 mW/m2 under identical conditions. Nystatin concentrations between 4 and 5 µg/mL maintain yeast viability at near-control levels, while higher concentrations cause a decrease in viability. These results demonstrate that controlled, sub-lethal membrane permeabilization combined with a dual-mediator strategy can enhance electron transfer in yeast-based biofuel cells.

Glucose imbalance in the human body is associated with multiple metabolic conditions such as hypoglycemia, hyperglycemia, insulin resistance, hyperinsulinemia, and diabetes. This review examines the latest developments in enzymatic glucose biosensors, with a focus on those utilizing nanocomposites and polymers. Conductive polymers, carbon nanostructures, metal nanoparticles, polymers with embedded metal nanoparticles, and polymeric ionic liquid-based structures are the most convenient for the design of electrochemical biosensors. Conductive polymer materials enhance electron transfer, improve biocompatibility, and enable flexible biosensor designs. Carbon nanostructures can be integrated with polymeric materials, improving the charge transfer. Polymer-metal structure-containing electrodes improve glucose sensor performance by enhancing conductivity and stability. Complex composite-based electrodes enable the exploitation of combinations of benefits provided by all previously mentioned materials. Significant progress in sensor performance was achieved by tailoring the composition and structure of these components.

Scanning electrochemical impedance microscopy (SEIM) was assessed as an electrochemical method for developing glucose biosensors based on glucose oxidase (GOx). To determine the lowest detectable GOx activity, scanning electrochemical microscopy (SECM) in the feedback mode (FB-SECM) was applied. During the measurement procedure, an ultramicroelectrode (UME) was moved vertically over the surface modified by immobilized GOx. A positive feedback response of the FB-SECM mode was determined during the assessment of surfaces modified by 5 fg/mm2 to 20 μg/mm2 surface concentration of GOx. The lowest surface concentration of GOx, which still provided reliable measurement results, was 50 fg/mm2. The approach curves registered using the FB-SECM mode were assessed using a mathematical model adapted for the calculation of reaction kinetics by SECM. According to this model, the reaction kinetics constant λ was calculated for differently modified surfaces in the presence of the same glucose concentration. For the surface not modified by GOx, the constant λ was determined to be 0.14, while for the GOx-modified surface λ gradually increased with increasing GOx surface concentrations, the λ value reached 0.34 when it was determined on the surfaces modified by 500 ng/mm2 of GOx. Any statistically significant changes in FB-SECM were detected when the surface concentration of GOx exceeded 50 pg/mm2. Notably, localized electrochemical impedance measurements using the SEIM mode enabled one to detect GOx activity even when GOx was immobilized on a nonconductive substrate surface. The results show that redox competition-based SEIM can be used to determine glucose concentrations in the range of 2-20 mM, while using 10 Hz AC perturbation. An FB-SECM configuration allows the reuse of the ultramicroelectrode while providing the localized impedance-based glucose concentration and enzyme activity measurements.

Scanning electrochemical microscopy (SECM) is a scanning probe microscope with an ultramicroelectrode (UME) as a probe. The technique is advantageous in the characterization of the electrochemical properties of surfaces. However, the limitations, such as slow imaging and many functions depending on the user, only allow us to use some of the possibilities. Therefore, we applied visual recognition and machine learning to detect micro-objects from the image and determine their electrochemical activity. The reconstruction of the image from several approach curves allows it to scan faster and detect active areas of the sample. Therefore, the scanning time and presence of the user is diminished. An automated scanning electrochemical microscope with visual recognition has been developed using commercially available modules, relatively low-cost components, design, software solutions proven in other fields, and an original control and data fusion algorithm.

The world's growing energy crisis demands renewable energy sources. This issue can be solved using microbial fuel cells (MFCs). MFCs are biocatalytic systems which convert chemical energy into electrical energy, thereby reducing pollution from hazardous chemical compounds. However, during the development of MFCs, one of the most significant challenges is finding and assessment of microorganisms that generate sufficient redox potential through metabolic and catalytic processes. In this research, we have used Ensifer meliloti (E. meliloti) bacteria to design MFCs based on consecutive action of two redox mediators (9,10 - phenanthrenequinone (PQ) and potassium ferricyanide), which transferred charge between E. meliloti bacteria and graphite rod electrode. A viability study of E. meliloti culture showed that PQ significantly inhibits the growth of bacteria at 0.036 mM. Cyclic voltammograms were registered in the presence of 20 mM of potassium ferricyanide and different concentrations (0.036 and 0.071 mM, 0.11 mM, 0.14 mM, 0.172 mM, 0.32 mM) of PQ. Four days of lasting assessment of the microbial fuel cells in two-electrode systems showed that the maximal open circuit potential during the experiment raised from 174.9 to 234.6 mV. Power increased from 0.392 to 0.741 mW m(-2).

In this paper, we provide a systematic review of atomic force microscopy (AFM), a fast-developing technique that embraces scanners, controllers, and cantilevers. The main objectives of this review are to analyze the available technical solutions of AFM, including the limitations and problems. The main questions the review addresses are the problems of working in contact, noncontact, and tapping AFM modes. We do not include applications of AFM but rather the design of different parts and operation modes. Since the main part of AFM is the cantilever, we focused on its operation and design. Information from scientific articles published over the last 5 years is provided. Many articles in this period disclose minor amendments in the mechanical system but suggest innovative AFM control and imaging algorithms. Some of them are based on artificial intelligence. During operation, control of cantilever dynamic characteristics can be achieved by magnetic field, electrostatic, or aerodynamic forces.

Scanning electrochemical microscopy is an advanced tool for studying electrochemically active surfaces, including biological ones. Experiments with biological systems must be performed fast since their reactions and states change very fast. SECM can be easily equipped with a top-mounted light microscope with a known distance between the probe and the camera. This hardware solution, in combination with machine learning algorithms, would allow for the automatic finding of target locations, selecting exact positions for measurements, and compensating for positioning inaccuracies. This article demonstrates a newly constructed SECM setup. In addition, it allows faster user adaptation to unknown topography and shortened scanning times.

Recently, the need to produce from soft materials or components in extra-large sizes has appeared, requiring special solutions that are affordable using industrial robots. Industrial robots are suitable for such tasks due to their flexibility, accuracy, and consistency in machining operations. However, robot implementation faces some limitations, such as a huge variety of materials and tools, low adaptability to environmental changes, flexibility issues, a complicated tool path preparation process, and challenges in quality control. Industrial robotics applications include cutting, milling, drilling, and grinding procedures on various materials, including metal, plastics, and wood. Advanced robotics technologies involve the latest advances in robotics, including integrating sophisticated control systems, sensors, data fusion techniques, and machine learning algorithms. These innovations enable robots to adapt better and interact with their environment, ultimately increasing their accuracy. The main focus of this study is to cover the most common industrial robotic machining processes and to identify how specific advanced technologies can improve their performance. In most of the studied literature, the primary research objective across all operations is to enhance the stiffness of the robotic arm’s structure. Some publications propose approaches for planning the robot’s posture or tool orientation. In contrast, others focus on optimizing machining parameters through the utilization of advanced control and computation, including machine learning methods with the integration of collected sensor data.

The impact of the energy consumption increase on the environment is one big problem, and it makes alternative energy sources so significant. Biological fuel cells (BFCs) based on enzymes and microorganisms are devices capable to directly transform chemical to electrical energy via electrochemical reactions involving biochemical pathways microbial biofuel cells (MBFCs). The study shows the possibility to use yeast-based MBFCs as the microorganisms for the quinones caused toxicity. Quinones are a controversial substance that is very important to MBFCs electrons transfer process but can cause oxidative and replicative stress of the cell. This is why the main aim of our research was to improve charge transfer efficiency in Baker’s yeast-based MBFCs by immobilizing quinones menadione (MD), 9, 10-phenantrenquinone (PQ), and MD/PQ on the anode surface. Metrohm μStat 400 Potentiostat/Galvanostat was used for the electrochemical measurements, which results are described in this paper.

Electrically conductive polymers are promising materials for charge transfer from living cells to the anodes of electrochemical biosensors and biofuel cells. The modification of living cells by polypyrrole (PPy) causes shortened cell lifespan, burdens the replication process, and diminishes renewability in the long term. In this paper, the viability and morphology non-modified, inactivated, and PPy-modified yeasts were evaluated. The results displayed a reduction in cell size, an incremental increase in roughness parameters, and the formation of small structural clusters of polymers on the yeast cells with the increase in the pyrrole concentration used for modification. Yeast modified with the lowest pyrrole concentration showed minimal change; thus, a microbial fuel cell (MFC) was designed using yeast modified by a solution containing 0.05 M pyrrole and compared with the characteristics of an MFC based on non-modified yeast. The maximal generated power of the modified system was 47.12 mW/m2, which is 8.32 mW/m2 higher than that of the system based on non-modified yeast. The open-circuit potentials of the non-modified and PPy-modified yeast-based cells were 335 mV and 390 mV, respectively. Even though applying a PPy layer to yeast increases the charge-transfer efficiency towards the electrode, the damage done to the cells due to modification with a higher concentration of PPy diminishes the amount of charge transferred, as the current density drops by 846 μA/cm2. This decrease suggests that modification by PPy may have a cytotoxic effect that greatly hinders the metabolic activity of yeast.

Over the past several decades, biology, chemistry, and medicine took advantage of gold nanoparticles (AuNPs) for their fascinating characteristics. Today these nanomaterials can be synthesized in various methods from biosynthesis, when particles are made by microbial culture, to physical. Using the fast scan cyclic voltammetry, AuNPs can be electrodeposited from chloroauric acid (HAuCl4) directly onto the surface of a graphite electrode. This method provides high reproducibility and allows to control the size of the nanoparticles (from 4 to 75 nm) and electrode coverage by changing HAuCl4 concentration, scan speed, and a number of applied cycles. Gold nanoparticles are known to express comparable catalytic activity to natural enzymes such as glucose oxidase or horseradish peroxidase. Despite the advantages over natural enzymes, inorganic enzyme mimicking catalysts exhibit limited catalytical efficiency and selectivity. To increase efficiency, we used low size AuNPs which increase reactivity; the lack of selectivity in a biofuel cell is advantageous since AuNPs can reduce/oxidize several substrates in the medium. Biofuel cell based on AuNP's has a superior life span, as the main active part of the system is inorganic, and thus it is not affected by oxygen stress, where typical microbial biofuel cells are struggling. The observed catalytic activity had a minimal dependency on temperature change. pH was changed from 4 to 10 with the smallest synthesized AuNPs. However, pH has an impact on the reaction speed. Results showed that biofuel cell is suitable for raw wastewater as it usually deviates from pH 7, and usable current can be generated.

Microbial fuel cell (MFC) efficiency depends on charge transfer capability from microbe to anode, and the application of suitable redox mediators is important in this area. In this study, yeast viability experiments were performed to determine the 2-methyl-1,4-naphthoquinone (menadione (MD)) influence on different yeast cell species (baker's yeast and Saccharomyces cerevisiae yeast cells). In addition, electrochemical measurements to investigate MFC performance and efficiency were carried out. This research revealed that baker's yeast cells were more resistant to dissolved MD, but the current density decreased when yeast solution concentration was incrementally increased in the same cell. The maximal calculated power of a designed baker's yeast-based MFC cell anode was 0.408 mW/m(2) and this power output was registered at 24 mV. Simultaneously, the cell generated a 62-mV open circuit potential in the presence of 23 mM potassium ferricyanide and the absence of glucose and immobilized MD. The results only confirm that MD has strong potential to be applied to microbial fuel cells and that a two-redox-mediator-based system is suitable for application in microbial fuel cells.

Scanning electrochemical microscopy enhanced by electrochemical impedance spectroscopy (SEIM) was applied to detect immobilized antibodies labelled with horseradish peroxidase (Ab-HRP). The localized HRP activity was investigated by the SEIM redox competition (RC-SEIM) mode using hydrogen peroxide as a substrate and hexacyanoferrate as a redox mediator. Electrochemical impedance shows to be related to the consumption of hydrogen peroxide at the ultramicroelectrode. For the evaluation of impedimetric results, an equivalent electric circuit was applied with solution resistance, double-layer capacitance, and charge-transfer resistance. These equivalent circuit characteristics depend on the distance between the sample and ultramicroelectrode, and the concentration of substrate. From the gathered data, the charge-transfer resistance appeared to be the parameter describing the behavior of HRP catalyzed reaction as it showed a linear dependence on H2O2 concentration. The RC-SEIM mode suitability for the studying of HRP catalyzed reactions and for the evaluation of Ab-HRP bound to the surface was demonstrated. Additionally, the applicability of RC-SEIM mode for the determination of Ab-HRP affinity bound to the target analyte was discussed.

Scanning probe microscope (SPM) positioning system quality depends on the design of the positioning system, environmental factors, frictional forces, and load. The aim of our research is to determine the accuracy and repeatability of a homemade micropositioning system for sample positioning in the experimental SPM setup. For the design of the micropositioning system, micrometric resolution ball-screw drives with stepper motors were used. Axes parameters, such as positioning errors, repeatability, and accuracy, were evaluated using the ISO 230–2 standard methodology. The results from experimental research show positioning accuracy of X-axis $\mathbf{113.67}\ \mu\mathbf{m}$, and repeatability $\mathbf{13.68}\ \mu\mathbf{m}$. Although the accuracy value mainly contains a systematic positioning error $\mathbf{103.5}\ \mu\mathbf{m}$, therefore, this can be compensated using features available in LinuxCNC control software. The positioning accuracy of the Y-axis was $\mathbf{6.86}\ \mu\mathbf{m}$, and repeatability $\mathbf{6.72}\ \mu\mathbf{m}$. Improvements in the mechanical components that make up the axis and additional research can improve the value of the repeatability of the X-axis of the system and the adaptability of the positioning system for SPM design.

Microbial fuel cells can be efficiently used for simultaneous cleaning of wastewater and generation of electricity. This research demonstrates the applicability of Baker yeast cells in the design of microbial biofuel cells. The applicability the 9,10-phenantrenequinone (PQ) as a redox mediator in the design of yeast-based microbial cell (MFC) for the improvement of charge transfer through the yeast cell membrane and cell wall towards the electrode was evaluated. The viability of bakers' yeast and pure Saccharomyces cerevisiae cell strains was investigated by evaluating the growth velocity of cells in the presence of a different concentration of PQ in solution. The growth curves of bakers' yeast showed that they were more resistant to PQ. Electrochemical measurements were performed with PQ as a redox mediator, which was (i) dissolved in solution and (ii) adsorbed on a graphite electrode. Differently modified graphite electrodes (namely: (i) non-modified, (ii) yeast-modified, (iii) modified by PQ and yeast) were evaluated. The modified electrodes were evaluated as anodes of MFC. The dependence of potential on external resistance and generated power of MFC was evaluated. Maximal open circuit potential was 178 mV at 7.8 mM of glucose and 23 mM of potassium ferricyanide. Maximal power of BFC calculated at the same conditions was registered at 56 mV, and it reached 22.2 mW/m(2) (at 30 mM of glucose). The application of PQ as a redox mediator for yeast-based MFC improves electron transfer through the yeast cell membrane and cell wall towards electrode without any noticeable decrease of yeast cell viability. (C) 2021 Elsevier Ltd. All rights reserved.

Human falls pose a serious threat to the person’s health, especially for the elderly and disease-impacted people. Early detection of involuntary human gait change can indicate a forthcoming fall. Therefore, human body fall warning can help avoid falls and their caused injuries for the skeleton and joints. A simple and easy-to-use fall detection system based on gait analysis can be very helpful, especially if sensors of this system are implemented inside the shoes without causing a sensible discomfort for the user. We created a methodology for the fall prediction using three specially designed Velostat®-based wearable feet sensors installed in the shoe lining. Measured pressure distribution of the feet allows the analysis of the gait by evaluating the main parameters: stepping rhythm, size of the step, weight distribution between heel and foot, and timing of the gait phases. The proposed method was evaluated by recording normal gait and simulated abnormal gait of subjects. The obtained results show the efficiency of the proposed method: the accuracy of abnormal gait detection reached up to 94%. In this way, it becomes possible to predict the fall in the early stage or avoid gait discoordination and warn the subject or helping companion person.

This research aimed to evaluate the toxic effect of multi-walled carbon nanotubes (MW-CNTs) on yeast cells in order to apply MW-CNTs for possible improvement of the efficiency of microbial biofuel cells. The SEM and XRD analysis suggested that here used MW-CNTs are in the range of 10–25 nm in diameter and their structure was confirmed by Raman spectroscopy. In this study, we evaluated the viability of the yeast Saccharomyces cerevisiae cells, affected by MW-CNTs, by cell count, culture optical density and atomic force microscopy. The yeast cells were exposed towards MW-CNTs (of 2, 50, 100 μg/mL concentrations in water-based solution) for 24 h. A mathematical model was applied for the evaluation of relative growth and relative death rates of yeast cells. We calculated that both of the rates are two times higher in the case if yeasts were treated by 50, 100 μg/mL of MW-CNTs containing solution, comparing to that treated by 0 and 2 μg/mL c of MW-CNTs containing solution. It was determined that the MW-CNTs have some observable effect upon the incubation of the yeast cells. The viability of yeast has decreased together with MW-CNTs concentration only after 5 h of the treatment. Therefore, we predict that the MW-CNTs can be applied for the modification of yeast cells in order to improve electrical charge transfer through the yeast cell membrane and/or the cell wall.

The increase in energy consumption also increases the damage to the environment and the toxicity of water still is one of the main problems in the world. Microbial fuel cells (MFCs) are one of the alternative energy sources. The study demonstrates the possibility to use yeast as a probe to assess redox and electrophile-based toxicities and to extend the life of a MFCs. But as it is known, the quinones cause the oxidative stress of the cells. That is why the main aim of our research was to create a real-time biomonitoring system using MFCs to detect the concentration of quinones in solution, using one and two redox mediator’s systems. Atomic force microscopy (AFM) was used to analyse the topography of the modified and non-modified graphite electrode and Potentiostat/Galvanostat Autolab PGSTAT 30 was used for the electrochemical measurements, which results are described in this paper.

Living cells mechanical properties establishment from Atomic force microscopy (AFM) force-separation curves is a challenge because the calculated Young’s modulus depends on the applied mathematical model. The more reliable results can be obtained using finite element models. In this work, yeast cells with different mechanical properties were measured by AFM. To change cells mechanical properties, yeasts were immersed in 9, 10-phenanthrenequinone, which changed cells’ membranes elasticity. 3D finite element model of the whole cell was created to calculate reacting force when AFM tip indents the cell in the same way as in the real experiment. It was found that our model is capable to draw the information about cells mechanical properties and visco-elastic behavior of cells membranes.