Bioimpedance Spectroscopy: Basics and Applications

Smart Bioimpedance Device for the Assessment of Peripheral Muscles in Patients with COPD

Muscle dysfunction and muscle atrophy are common complications resulting from Chronic Obstructive Pulmonary Disease (COPD). The evaluation of the peripheral muscles can be carried out through the assessment of their structural components from ultrasound images or their functional components through isometric and isotonic strength tests. This evaluation, performed mainly on the quadriceps muscle, is not only of great interest for diagnosis, prognosis and monitoring of COPD, but also for the evaluation of the benefits of therapeutic interventions. In this work, bioimpedance spectroscopy technology is proposed as a low-cost and easy-to-use alternative for the evaluation of peripheral muscles, becoming a feasible alternative to ultrasound images and strength tests for their application in routine clinical practice. For this purpose, a laboratory prototype of a bioimpedance device has been adapted to perform segmental measurements in the quadriceps region. The validation results obtained in a pseudo-randomized study in patients with COPD in a controlled clinical environment which involved 33 volunteers confirm the correlation and correspondence of the bioimpedance parameters with respect to the structural and functional parameters of the quadriceps muscle, making it possible to propose a set of prediction equations. The main contribution of this manuscript is the discovery of a linear relationship between quadriceps muscle properties and the bioimpedance Cole model parameters, reaching a correlation of 0.69 and an average error of less than 0.2 cm regarding the thickness of the quadriceps estimations from ultrasound images, and a correlation of 0.77 and an average error of 3.9 kg regarding the isometric strength of the quadriceps muscle.

Reproducibility analysis of bioimpedance-based self-developed live cell assays

Bioimpedance spectrum (BIS) measurements have a great future in in vitro experiments, meeting all the requirements for non-destructive and label-free methods. Nevertheless, a real basic research can provide the necessary milestones to achieve the success of the method. In this paper a self-developed technology-based approach for in vitro assays is proposed. Authors invented a special graphene-based measuring plate in order to assess the high sensitivity and reproducibility of introduced technique. The design of the self-produced BIS plates maximizes the detection capacity of qualitative changes in cell culture and it is robust against physical effects and artifacts. The plates do not influence the viability and proliferation, however the results are robust, stable and reproducible regardless of when and where the experiments are carried out. In this study, physiological saline concentrations, two cancer and stem cell lines were utilized. All the results were statistically tested and confirmed. The findings of the assays show, that the introduced BIS technology is appropriate to be used in vitro experiments with high efficacy. The experimental results demonstrate high correlation values across the replicates, and the model parameters suggested that the characteristic differences among the various cell lines can be detected using appropriate hypothesis tests.

Advances in Material-Assisted Electromagnetic Neural Stimulation

Bioelectricity plays a crucial role in organisms, being closely connected to neural activity and physiological processes. Disruptions in the nervous system can lead to chaotic ionic currents at the injured site, causing disturbances in the local cellular microenvironment, impairing biological pathways, and resulting in a loss of neural functions. Electromagnetic stimulation has the ability to generate internal currents, which can be utilized to counter tissue damage and aid in the restoration of movement in paralyzed limbs. By incorporating implanted materials, electromagnetic stimulation can be targeted more accurately, thereby significantly improving the effectiveness and safety of such interventions. Currently, there have been significant advancements in the development of numerous promising electromagnetic stimulation strategies with diverse materials. This review provides a comprehensive summary of the fundamental theories, neural stimulation modulating materials, material application strategies, and pre-clinical therapeutic effects associated with electromagnetic stimulation for neural repair. It offers a thorough analysis of current techniques that employ materials to enhance electromagnetic stimulation, as well as potential therapeutic strategies for future applications.

Integrating classification and regression learners with bioimpedance methods for estimating weight status in infants and juveniles from the southern Cuba region

OBJECTIVE

The search for other indicators to assess the weight and nutritional status of individuals is important as it may provide more accurate information and assist in personalized medicine. This work is aimed to develop a machine learning predictions of weigh status derived from bioimpedance measurements and other physical parameters of healthy younger volunteers from Southern Cuba Region.

METHODS

A pilot random study at the Pediatrics Hospital was conducted. The volunteers were selected between 2002 and 2008, ranging in age between 2 and 18 years old. In total, 776 female and male volunteers are studied. Along the age and sex in the cohort, volunteers with class I obesity, overweight, underweight and with normal weight are considered. The bioimpedance parameters are obtained by measuring standard tetrapolar whole-body configuration. The bioimpedance analyser is used, collecting fundamental bioelectrical and other parameters of interest. A classification model are performed, followed by a prediction of the body mass index.

RESULTS

The results derived from the classification leaner reveal that the size, body density, phase angle, body mass index, fat-free mass, total body water volume according to Kotler, body surface area, extracellular water according to Kotler and sex largely govern the weight status of this population. In particular, the regression model shows that other bioparameters derived from impedance measurements can be associated with weight status estimation with high accuracy.

CONCLUSION

The classification and regression predictive models developed in this work are of the great importance to assist the diagnosis of weigh status with high accuracy. These models can be used for prompt weight status evaluation of younger individuals at the Pediatrics Hospital in Santiago de Cuba, Cuba.

The role of various physiological and bioelectrical parameters for estimating the weight status in infants and juveniles cohort from the Southern Cuba region: a machine learning study

OBJECTIVE

The search for other indicators to assess the weight status of individuals is important as it may provide more accurate information and assist in personalized medicine.This work is aimed to develop a machine learning predictions of weigh status derived from bioimpedance measurements and other physical parameters of healthy infant juvenile cohort from the Southern Cuba Region, Santiago de Cuba.

METHODS

The volunteers were selected between 2002 and 2008, ranging in age between 2 and 18 years old. In total, 393 female and male infant and juvenile individuals are studied. The bioimpedance parameters are obtained by measuring standard tetrapolar whole-body configuration. A classification model are performed, followed by a prediction of other bioparameters influencing the weight status.

RESULTS

The results obtained from the classification model indicate that fat-free mass, reactance, and corrected resistance primarily influence the weight status of the studied population. Specifically, the regression model demonstrates that other bioparameters derived from impedance measurements can be highly accurate in estimating weight status.

CONCLUSION

The classification and regression predictive models developed in this work are of the great importance for accessing to the weigh status with high accuracy of younger individuals at the Oncological Hospital in Santiago de Cuba, Cuba.

Improved bioimpedance spectroscopy tissue classification through data augmentation from generative adversarial networks

Bioimpedance spectroscopy is a tissue classification technique with many clinical applications. Similarly to other data-driven methods, it requires large amounts of data to accurately distinguish similar classes of tissue. Classifiers trained on small datasets typically suffer from over-fitting and lack the ability to generalise to previously unseen data. However, a large in or ex vivo spectral database is difficult to attain. Data collection is usually limited to studies that occur infrequently, and publicly available data is often not available. A solution to this problem is to artificially increase the training dataset by creating modified, yet accurate, copies of the original dataset. The most common techniques in spectral classification are to add noise to copies of the original data, over-sample it, or randomly interpolate pairs of the original data. However, simply perturbing or interpolating the data does not guarantee that the new dataset captures the key features of the original data needed for accurate classification. This study proposes a novel way to augment bioimpedance spectral data. It uses generative adversarial networks (GAN)-a model in which two neural networks (NN) compete with each other: while one NN artificially manufactures data that could be mistaken for real data, the role of the second NN is to identify which data it receives has been artificially created. The first NN then interactively adapts its output until the second NN can no longer flag artificially created data. The result is a new dataset that truly represents the features of the original data. In this study, three GAN architectures are used, i.e., the vanilla GAN, the deep convolutional GAN, and the Wasserstein GAN. Then, the generated data is used to train five classification methods, and their results are compared to a baseline that only uses the original data. The results from a dataset of 13 different tissue classes show that the deep convolutional GAN is most statistically similar to the original data and improves classification accuracy by 15% when compared to the same model trained only on the original data. The Wasserstein-GAN architecture also provides significant improvements of up to 24% better accuracy.

Efficacy and safety of zibotentan and dapagliflozin in patients with chronic kidney disease: study design and baseline characteristics of the ZENITH-CKD trial

BACKGROUND

Sodium-glucose co-transporter 2 inhibitors (SGLT2is) are part of the standard of care for patients with chronic kidney disease (CKD), both with and without type 2 diabetes. Endothelin A (ETA) receptor antagonists have also been shown to slow progression of CKD. Differing mechanisms of action of SGLT2 and ETA receptor antagonists may enhance efficacy. We outline a study to evaluate the effect of combination zibotentan/dapagliflozin versus dapagliflozin alone on albuminuria and estimated glomerular filtration rate (eGFR).

METHODS

We are conducting a double-blind, active-controlled, Phase 2b study to evaluate the efficacy and safety of ETA receptor antagonist zibotentan and SGLT2i dapagliflozin in a planned 415 adults with CKD (Zibotentan and Dapagliflozin for the Treatment of CKD; ZENITH-CKD). Participants are being randomized (1:2:2) to zibotentan 0.25 mg/dapagliflozin 10 mg once daily (QD), zibotentan 1.5 mg/dapagliflozin 10 mg QD and dapagliflozin 10 mg QD alone, for 12 weeks followed by a 2-week off-treatment wash-out period. The primary endpoint is the change in log-transformed urinary albumin-to-creatinine ratio (UACR) from baseline to Week 12. Other outcomes include change in blood pressure from baseline to Week 12 and change in eGFR the study. The incidence of adverse events will be monitored. Study protocol-defined events of special interest include changes in fluid-related measures (weight gain or B-type natriuretic peptide).

RESULTS

A total of 447 patients were randomized and received treatment in placebo/dapagliflozin (n = 177), zibotentan 0.25 mg/dapagliflozin (n = 91) and zibotentan 1.5 mg/dapagliflozin (n =  179). The mean age was 62.8 years, 30.9% were female and 68.2% were white. At baseline, the mean eGFR of the enrolled population was 46.7 mL/min/1.73 m2 and the geometric mean UACR was 538.3 mg/g.

CONCLUSION

This study evaluates the UACR-lowering efficacy and safety of zibotentan with dapagliflozin as a potential new treatment for CKD. The study will provide information about an effective and safe zibotentan dose to be further investigated in a Phase 3 clinical outcome trial.

CLINICAL TRIAL REGISTRATION NUMBER

NCT04724837.

Electrical bioimpedance analysis and comparison in biological tissues through crystalloid solutions implementation

Electrical bioimpedance is a non-invasive and radiation-free technique that was proposed to be used in different clinical areas, however, its practical use is limited due to its low capacity to discriminate between tissues. In order to overcome this limitation, our research group proposes to incorporate the contrast media into the electrical bioimpedance procedure. The main objective of the present study was to assess the crystalloid solutions as a possible contrast media to discriminate between different tissue types in the bioimpedance technique. Two medical-grade crystalloid solutions (Hartmann and NaCl 0.9%) were injected into three biological ex vivo models: kidney, liver, and brain. BIOPAC system was used to acquire bioimpedance data before and after the injections. The data was adjusted to the Debye electrical model. The analysis of measured values showed substantial bioimpedance disparities in tissues subjected to isotonic solutions. The NaCl solution exhibited more pronounced changes in electrical parameters compared to the Hartmann solution. Similarly, NaCl solution displayed superior discriminatory capabilities among tissues, with variations of 465%, 157%, and 206%. Distinct spectral modifications were identified, with tissues demonstrating unique responses at each frequency of analysis relative to untreated tissue. Variations in bandwidth alterations were discernible among tissues, providing clear distinctions. In conclusion, the research showed that the crystalloid solution exhibited greater sensitivity and superior tissue contrast at specific frequencies. This study's findings underscore the feasibility of implementing crystalloid solutions to enhance tissue discrimination, similar to the effects of contrast agents.

Recent Development of Implantable Chemical Sensors Utilizing Flexible and Biodegradable Materials for Biomedical Applications

Implantable chemical sensors built with flexible and biodegradable materials exhibit immense potential for seamless integration with biological systems by matching the mechanical properties of soft tissues and eliminating device retraction procedures. Compared with conventional hospital-based blood tests, implantable chemical sensors have the capability to achieve real-time monitoring with high accuracy of important biomarkers such as metabolites, neurotransmitters, and proteins, offering valuable insights for clinical applications. These innovative sensors could provide essential information for preventive diagnosis and effective intervention. To date, despite extensive research on flexible and bioresorbable materials for implantable electronics, the development of chemical sensors has faced several challenges related to materials and device design, resulting in only a limited number of successful accomplishments. This review highlights recent advancements in implantable chemical sensors based on flexible and biodegradable materials, encompassing their sensing strategies, materials strategies, and geometric configurations. The following discussions focus on demonstrated detection of various objects including ions, small molecules, and a few examples of macromolecules using flexible and/or bioresorbable implantable chemical sensors. Finally, we will present current challenges and explore potential future directions.

A Pilot Study Examining the Dielectric Response of Human Forearm Tissues

This work aims to describe the dielectric behaviors of four main tissues in the human forearm using mathematical modelling, including fat, muscle, blood and bone. Multi-frequency bioimpedance analysis (MF-BIA) was initially performed using the finite element method (FEM) with a 3D forearm model to estimate impedance spectra from 10 kHz to 1 MHz, followed by a pilot study involving two healthy subjects to characterize the response of actual forearm tissues from 1 kHz to 349 kHz. Both the simulation and experimental results were fitted to a single-dispersion Cole model (SDCM) and a multi-dispersion Cole model (MDCM) to determine the Cole parameters for each tissue. Cole-type responses of both simulated and actual human forearms were observed. A paired t-test based on the root mean squared error (RMSE) values indicated that both Cole models performed comparably in fitting both simulated and measured bioimpedance data. However, MDCM exhibited higher accuracy, with a correlation coefficient (R2) of 0.99 and 0.89, RMSE of 0.22 Ω and 0.56 Ω, mean difference (mean ± standard deviation) of 0.00 ± 0.23 Ω and -0.28 ± 0.23 Ω, and mean absolute error (MAE) of 0.0007 Ω and 0.2789 Ω for the real part and imaginary part of impedance, respectively. Determining the electrical response of multi-tissues can be helpful in developing physiological monitoring of an organ or a section of the human body through MF-BIA and hemodynamic monitoring by filtering out the impedance contributions from the surrounding tissues to blood-flow-induced impedance variations.

Conformal Temperature/Impedance Sensing Patch Based on Graphene Materials for Nondestructive Detection of Fish Freshness

Rapid nondestructive detection of fish freshness is essential to ensure food safety and nutrition. In this study, we demonstrate a conformal temperature/impedance sensing patch for temperature monitoring, as well as freshness classification during fish storage. The optimization of the flexible laser-induced graphene electrodes is studied based on both simulation and experimental validation, and dimensional accuracy of 5‰ and high impedance reproducibility are obtained. A laser-assisted thermal reduction technology is innovatively introduced to directly form a reduced graphene oxide-based temperature-sensitive layer on the surface of a flexible substrate. The comprehensive performance is superior to that of most reported temperature-sensitive devices based on graphene materials. As an application demonstration, the fabricated flexible dual-parameter sensing patch is conformed to the surface of a refrigerated fish. The patch demonstrates the ability to accurately sense low temperatures in a continuous 120 min monitoring, accompanied by no interference from high humidity. Meanwhile, the collected impedance data are imported into the support vector machine model to obtain a freshness classification accuracy of 93.07%. The conformal patch integrated with crosstalk-free dual functions costs less than $1 and supports free customization, providing a feasible methodology for rapid nondestructive detection or monitoring of food quality.

Smart Implant with Bacteria Monitoring and Killing Ability for Orthopedic Applications

Bacterial infections around implants constitute a significant cause of implant failures. Early recognition of bacterial adhesion is an essential factor in preventing implant infections. Therefore, an implant capable of detecting and disinfecting initial bacterial adhesion is required. This study reports on the development of an intelligent solution for this issue. We developed an implant integrated with a biosensor electrode based on alternating current (AC) impedance technology to monitor the early growth process of Escherichia coli (E. coli) and its elimination. The biosensor electrode was fabricated by coating polypyrrole (PPy) doped with sodium p-toluenesulfonate (TSONa) on titanium (Ti) surfaces. Monitoring the change in resistance using electrochemical impedance spectroscopy (EIS), combined with an equivalent circuit model (ECM), enables the monitoring of the early adhesion of E. coli. The correlation with the classical optical density (OD) monitoring value reached 0.989. Subsequently, the eradication of bacteria on the electrode surface was achieved by applying different voltages to E. coli cultured on the electrode surface, which caused damage to E. coli. Furthermore, in vitro cellular experiments showed that the PPy coating has good biocompatibility and can promote bone differentiation.

A Microfluidic Device for Tobacco Ringspot Virus Detection by Electrochemical Impedance Spectroscopy

Aiming at the problem of how to achieve the rapid detection of pathogenic microorganisms, this paper takes tobacco ringspot virus as the detection object, designs the impedance detection and analysis platform of tobacco ringspot virus based on microfluidic impedance method, establishes an equivalent circuit model to analyze the experimental results, and determines the optimal detection frequency of tobacco ringspot virus detection. Based on this frequency, an impedance-concentration regression model was established for the detection of tobacco ringspot virus in a tobacco ringspot virus detection device. Based on this model, a tobacco ringspot virus detection device was designed by using an AD5933 impedance detection chip. A comprehensive test study was carried out on the developed tobacco ringspot virus detection device through various testing methods, which verified the feasibility of the tobacco ringspot virus detection device and provided technical support for the field detection of pathogenic microorganisms.

Cellular electrical impedance to profile SARS-CoV-2 fusion inhibitors and to assess the fusogenic potential of spike mutants

Despite the vaccination campaigns for COVID-19, we still cannot control the spread of SARS-CoV-2, as evidenced by the ongoing circulation of the Omicron variants of concern. This highlights the need for broad-spectrum antivirals to further combat COVID-19 and to be prepared for a new pandemic with a (re-)emerging coronavirus. An interesting target for antiviral drug development is the fusion of the viral envelope with host cell membranes, a crucial early step in the replication cycle of coronaviruses. In this study, we explored the use of cellular electrical impedance (CEI) to quantitatively monitor morphological changes in real time, resulting from cell-cell fusion elicited by SARS-CoV-2 spike. The impedance signal in CEI-quantified cell-cell fusion correlated with the expression level of SARS-CoV-2 spike in transfected HEK293T cells. For antiviral assessment, we validated the CEI assay with the fusion inhibitor EK1 and measured a concentration-dependent inhibition of SARS-CoV-2 spike mediated cell-cell fusion (IC₅₀ value of 0.13 μM). In addition, CEI was used to confirm the fusion inhibitory activity of the carbohydrate-binding plant lectin UDA against SARS-CoV-2 (IC₅₀ value of 0.55 μM), which complements prior in-house profiling activities. Finally, we explored the utility of CEI in quantifying the fusogenic potential of mutant spike proteins and in comparing the fusion efficiency of SARS-CoV-2 variants of concern. In summary, we demonstrate that CEI is a powerful and sensitive technology that can be applied to studying the fusion process of SARS-CoV-2 and to screening and characterizing fusion inhibitors in a label-free and non-invasive manner.

Design and Modeling of a Device Combining Single-Cell Exposure to a Uniform Electrical Field and Simultaneous Characterization via Bioimpedance Spectroscopy

Previous studies have demonstrated the electropermeabilization of cell membranes exposed to an electric field with moderate intensity (<2 V/cm) and a frequency of <100 MHz. Bioimpedance spectroscopy (BIS) is an electrical characterization technique that can be useful in studying this phenomenon because it is already used for electroporation. In this paper, we report a device designed to perform BIS on single cells and expose them to an electric field simultaneously. It also allows cells to be monitored by visualization through a transparent exposure electrode. This device is based on a lab-on-a-chip (LOC) with a microfluidic cell-trapping system and microelectrodes for BIS characterization. We present numerical simulations that support the design of the LOC. We also describe the fabrication of the LOC and the first electrical characterization of its measurement bandwidth. This first test, performed on reference medium with a conductivity in the same order than human cells, confirms that the measurement capabilities of our device are suitable for electrical cells characterization.

Reliable impedance analysis of Li-ion battery half-cell by standardization on electrochemical impedance spectroscopy (EIS)

Electrochemical impedance spectroscopy (EIS) is a powerful characterization technique for the in-depth investigation of kinetic/transport parameters detection, reaction mechanism understanding, and degradation effects exploration in lithium-ion battery (LIB) systems. However, due to the lack of standardized criterion/paradigm, severe misinterpretations occur frequently during an EIS measurement. In this paper, the significance of instrumental accuracy is described and the character/principle of selection on the simulation model is illuminated/proposed, showing that an adequate precision device and an appropriate fitting model are a prerequisite for a correct EIS analysis. Moreover, the drawbacks of conventional two-electrode EIS experiments for typical coin-type cells are rigorously pointed out by comparison with the ideal three-electrode configuration, where the real impedance information of the cathode would be masked by the sum of both the anode film resistance response and the unavoidable inductive loop signal. The three-electrode case enables efficient accurate observations on individual electrodes, thus facilitating abundant and useful information acquisition. Consequently, devices with a sufficient accuracy, rational simulation models, and advanced three-electrode cells are distinctly illustrated as standardized criterion/paradigm for EIS characterizations, which are essentially important for electrode and interface modifications in LIBs.

Impact of Age and Sex on Electrical Impedance Values in Healthy Oral Mucosa

Background: Electrical impedance (EI) is a property of all living tissues and represents the resistance to the electric current flow through a living tissue. EI depends on the structure and chemical composition of the tissue. The aim of this study was to determine the influence of age, sex, and electrode pressure on the EI values of healthy oral mucosa. The study involved 101 participants with healthy oral mucosa who were divided into three age groups. EI was measured in seven anatomical regions. Results: Significant differences between different age groups were found. Younger participants (20–40 years) had significantly higher EI values than the older participants (60+). Significantly higher EI values were found in women at all localisations at all measured frequencies, except on the hard palate. EI values measured with higher sub-pressure were significantly lower than values measured with lower sub-pressure at all frequencies and localisations, except the tongue dorsum, tongue border, and sublingual mucosa. Conclusions: This study found that EI values in healthy oral mucosa depend on age and sex and may also depend on the pressure of the measuring device. These factors should be kept in mind when EI is used as a diagnostic method for different oral lesions.

In-Depth Characterization of Zika Virus Inhibitors Using Cell-Based Electrical Impedance

In this study, we use electric cell-substrate impedance sensing (ECIS), an established cell-based electrical impedance (CEI) technology, to decipher the kinetic cytopathic effect (CPE) induced by Zika virus (ZIKV) in susceptible human A549 lung epithelial cells and to evaluate several classes of compounds with reported antiviral activity (two entry inhibitors and two replication inhibitors). To validate the assay, we compare the results with those obtained with more traditional in vitro methods based on cell viability and viral yield readouts. We demonstrate that CEI can detect viral infection in a sensitive manner and can be used to determine antiviral potency. Moreover, CEI has multiple benefits compared to conventional assays: the technique is less laborious and better at visualizing the dynamic antiviral activity profile of the compounds, while also it has the ability to determine interesting time points that can be selected as endpoints in assays without continuous readout. We describe several parameters to characterize the compounds' cytotoxicity and their antiviral activity profile. In addition, the CEI patterns provide valuable additional information about the presumed mechanism of action of these compounds. Finally, as a proof of concept, we used CEI to evaluate the antiviral activity of a small series of compounds, for which we demonstrate that the sulfonated polymer PRO2000 inhibits ZIKV with a response profile representative for a viral entry inhibitor. Overall, we demonstrate for the first time that CEI is a powerful technology to evaluate and characterize compounds against ZIKV replication in a real-time, label-free, and noninvasive manner. IMPORTANCE Zika virus can cause serious disease in humans. Unfortunately, no antiviral drugs are available to treat infection. Here, we use an impedance-based method to continuously monitor virus infection in-and damage to-human cells. We can determine the Zika viral dose with this technique and also evaluate whether antiviral compounds protect the cells from damage caused by virus replication. We also show that this technique can be used to further unravel the characteristics of these compounds, such as their toxicity to the cells, and that it might even give further insight in their mechanism of antiviral action. Finally, we also find a novel Zika virus inhibitor, PRO2000. Overall, in this study, we use the impedance technology to-for the first time-evaluate compounds with anti-Zika virus properties, and therefore it can add valuable information in the further search for antiviral drugs.

Copper–Ruthenium Composite as Perspective Material for Bioelectrodes: Laser-Assisted Synthesis, Biocompatibility Study, and an Impedance-Based Cellular Biosensor as Proof of Concept

Copper is an inexpensive material that has found wide application in electronics due to its remarkable electric properties. However, the high toxicity of both copper and copper oxide imposes restrictions on the application of this metal as a material for bioelectronics. One way to increase the biocompatibility of pure copper while keeping its remarkable properties is to use copper-based composites. In the present study, we explored a new copper–ruthenium composite as a potential biocompatible material for bioelectrodes. Sample electrodes were obtained by subsequent laser deposition of copper and ruthenium on glass plates from a solution containing salts of these metals. The fabricated Cu–Ru electrodes exhibit high effective area and their impedance properties can be described by simple R-CPE equivalent circuits that make them perspective for sensing applications. Finally, we designed a simple impedance cell-based biosensor using this material that allows us to distinguish between dead and alive HeLa cells.

Magnetoimpedance Biosensors and Real-Time Healthcare Monitors: Progress, Opportunities, and Challenges

A small DC magnetic field can induce an enormous response in the impedance of a soft magnetic conductor in various forms of wire, ribbon, and thin film. Also known as the giant magnetoimpedance (GMI) effect, this phenomenon forms the basis for the development of high-performance magnetic biosensors with magnetic field sensitivity down to the picoTesla regime at room temperature. Over the past decade, some state-of-the-art prototypes have become available for trial tests due to continuous efforts to improve the sensitivity of GMI biosensors for the ultrasensitive detection of biological entities and biomagnetic field detection of human activities through the use of magnetic nanoparticles as biomarkers. In this review, we highlight recent advances in the development of GMI biosensors and review medical devices for applications in biomedical diagnostics and healthcare monitoring, including real-time monitoring of respiratory motion in COVID-19 patients at various stages. We also discuss exciting research opportunities and existing challenges that will stimulate further study into ultrasensitive magnetic biosensors and healthcare monitors based on the GMI effect.

Improving FPGA Based Impedance Spectroscopy Measurement Equipment by Means of HLS Described Neural Networks to Apply Edge AI

The artificial intelligence (AI) application in instruments such as impedance spectroscopy highlights the difficulty to choose an electronic technology that correctly solves the basic performance problems, adaptation to the context, flexibility, precision, autonomy, and speed of design. Present work demonstrates that FPGAs, in conjunction with an optimized high-level synthesis (HLS), allow us to have an efficient connection between the signals sensed by the instrument and the artificial neural network-based AI computing block that will analyze them. State-of-the-art comparisons and experimental results also demonstrate that our designed and developed architectures offer the best compromise between performance, efficiency, and system costs in terms of artificial neural networks implementation. In the present work, computational efficiency above 21 Mps/DSP and power efficiency below 1.24 mW/Mps are achieved. It is important to remark that these results are more relevant because the system can be implemented on a low-cost FPGA.

Intraoperative pathologically-calibrated diagnosis of lymph nodes involved by breast cancer cells based on electrical impedance spectroscopy; a prospective diagnostic human model study

BACKGROUND

Nodal status evaluation is a crucial step in determining prognostic factors and managing treatment strategies for breast cancer patients. Preoperative (CNB), intraoperative (SLNB), and even postoperative techniques (Formalin-Fixed Paraffin-Embedded sectioning, FFPE) have definite limitations of precision or sometimes are time-consuming for the result declaration. The primary purpose of this prospective study is to provide a precise complementary system for distinguishing lymph nodes (LNs) involved by cancerous cells in breast cancer patients intraoperatively.

METHODS

The proposed system, Electrical Lymph Scoring(ELS), is designed based on the dielectric properties of the under-test LNs. The system has a needle-shaped 2-electrode probe entered into SLNs or ALNs dissected from patients through standard surgical guidelines. Impedance magnitude in f = 1 kH (Z_1kHz) and Impedance Phase Slope in frequency ranges of 100 kHz-500 kHz (IPS) were then extracted from the impedance spectroscopy data in a cohort study of 77 breast cancer patients(totally 282 dissected LNs) who had been undergone surgery before (n = 55) or after (n = 22) chemical therapies (non-neoadjuvant or neoadjuvant chemotherapy). A new admittance parameter(Y_n^') also proposed for LN detection in neoadjuvant chemotherapy patients.

RESULTS

Considering the permanent pathology result as the gold standard checked by two independent expert pathologists, a significant correlation was observed between the presence of cancerous cells in LNs and individual ranges of the ELS electrical responses. Compared with normal LNs containing fatty ambient and immune cells, LNs involved by cancerous clusters would reduce the Z_1kHz and increase the IPS. These changes correlate with fat metabolism by cancer cells due to their Fatty Acid Oxidation (FAO) in LN, which results in different dielectric properties between high and low-fat content of normal and cancerous LNs, respectively.

CONCLUSIONS

By finding the best correlation between our defined impedimetric parameters and pathological states of tested LNs, a real-time intraoperative detection approach was developed for highly-sensitive (92%, P<0.001) diagnosis of involved sentinel or axillary LNs. The impact of real-time intraoperative scoring of SLNs would make a pre-estimation about the necessity of excising further LNs to help the surgeon for less invasive surgery, especially in the absence of frozen-section equipment.

A Frequency Domain Analysis of the Excitability and Bifurcations of the FitzHugh-Nagumo Neuron Model

The dynamics of neurons consist of oscillating patterns of a membrane potential that underpin the operation of biological intelligence. The FitzHugh-Nagumo (FHN) model for neuron excitability generates rich dynamical regimes with a simpler mathematical structure than the Hodgkin-Huxley model. Because neurons can be understood in terms of electrical and electrochemical methods, here we apply the analysis of the impedance response to obtain the characteristic spectra and their evolution as a function of applied voltage. We convert the two nonlinear differential equations of FHN into an equivalent circuit model, classify the different impedance spectra, and calculate the corresponding trajectories in the phase plane of the variables. In analogy to the field of electrochemical oscillators, impedance spectroscopy detects the Hopf bifurcations and the spiking regimes. We show that a neuron element needs three essential internal components: capacitor, inductor, and negative differential resistance. The method supports the fabrication of memristor-based artificial neural networks.

Metal-Mediated Nanoscale Cerium Oxide Inactivates Human Coronavirus and Rhinovirus by Surface Disruption

The COVID19 pandemic has brought global attention to the threat of emerging viruses and to antiviral therapies, in general. In particular, the high transmissibility and infectivity of respiratory viruses have been brought to the general public's attention, along with the need for highly effective antiviral and disinfectant materials/products. This study has developed two distinct silver-modified formulations of redox-active nanoscale cerium oxide (AgCNP1 and AgCNP2). The formulations show specific antiviral activities toward tested OC43 coronavirus and RV14 rhinovirus pathogens, with materials characterization demonstrating a chemically stable character for silver nanophases on ceria particles and significant differences in Ce3+/Ce4+ redox state ratio (25.8 and 53.7% Ce3+ for AgCNP1 & 2, respectively). In situ electrochemical studies further highlight differences in formulation-specific viral inactivation and suggest specific modes of action. Altogether, the results from this study support the utility of AgCNP formulations as high stability, high efficacy materials for use against clinically relevant virus species.

Impedance Spectroscopy Dynamics of Biological Neural Elements: From Memristors to Neurons and Synapses

Understanding the operation of neurons and synapses is essential to reproducing biological computation. Building artificial neuromorphic networks opens the door to a new generation of faster and low-energy-consuming electronic circuits for computation. The main candidates to imitate the natural biocomputation processes, such as the generation of action potentials and spiking, are memristors. Generally, the study of the performance of material neuromorphic elements is done by the analysis of time transient signals. Here, we present an analysis of neural systems in the frequency domain by small-amplitude ac impedance spectroscopy. We start from the constitutive equations for the conductance and memory effect, and we derive and classify the impedance spectroscopy spectra. We first provide a general analysis of a memristor and demonstrate that this element can be expressed as a combination of simple parts. In particular, we derive a basic equivalent circuit where the memory effect is represented by an RL branch. We show that this ac model is quite general and describes the inductive/negative capacitance response in many systems such as halide perovskites and organic LEDs. Thereafter, we derive the impedance response of the integrate-and-fire exponential adaptative neuron model that introduces a negative differential resistance and a richer set of spectra. On the basis of these insights, we provide an interpretation of the varied spectra that appear in the more general Hodgkin-Huxley neuron model. Our work provides important criteria to determine the properties that must be found in material realizations of neuronal elements. This approach has the great advantage that the analysis of highly complex phenomena can be based purely on the shape of experimental impedance spectra, avoiding the need for specific modeling of rather involved material processes that produce the required response.

Impedance Spectroscopy and ac Conductivity in Ba0.5Sr0.5TiO3-Ca10(PO4)6(OH)2 Ceramic Composites: An Electrical Approach to Unveil Biocomposites

We report bioceramic composites of varying concentrations of Ba_0.5Sr_0.5TiO₃ (BST) and Ca₁₀(PO₄)₆(OH)₂ (HAP) for the analysis of electrical properties. The motivation is to predict the suitability of the composites for bio-electrets or the practical possibility in designing electro-active scaffolds. X-ray diffraction (XRD) and field-emission scanning electron microscopy (FESEM) are used to analyze the microstructural evolution of the composites. A systematic variation in the grain and crystallite sizes is noticed from the FESEM and XRD, along with the presence of Sr₅(PO₄)₃(OH) (SAP). The temperature and frequency variations of the dielectric properties of the composites are studied. Modeling of the dielectric properties with the microstructural properties and at. % of the monolith BST is presented. Cole-Cole formalism is adopted to model the electrical behavior of the synthesized composites. Furthermore, the ac conductivity analysis reveals that Mott's variable range hopping (VRH) conduction is the most appropriate formalism that successfully describes the conduction process. The established Mott's VRH is also related to the polarization mechanisms active in the specimens. Our study projects a correlation between the electrical and biological properties by predicting the protein adsorption behavior from the perspective of impedance spectroscopy.