A hybrid Genetic Algorithm and Levenberg-Marquardt (GA-LM) method for cell suspension measurement with electrical impedance spectroscopy

Exploring the role of impedance spectroscopy in assessing 405 nm laser-induced inactivation of saccharomyces cerevisiae

Impedance spectroscopy was employed to assess the electrical properties of yeast following 405 nm laser irradiation, exploring the effects of visible, non-ionizing laser-induced inactivation as a more selective and safer alternative for photoinactivation applications compared to the use of DNA targeting, ionizing UV light. Capacitance and impedance spectra were obtained for yeast suspensions irradiated for 10, 20, 30, and 40 min using 100 and 200 mW laser powers. Noticeable differences in capacitance spectra were observed at lower frequencies (40 Hz to 1 kHz), with a significant increase at 40 min for both laser powers. β-dispersion was evident in the impedance spectra in the frequency range of 10 kHz to 10 MHz. The characteristic frequency of dielectric relaxation steadily shifted to higher frequencies with increasing irradiation time, with a drastic change observed at 40 min for both laser powers. These changes signify a distinct alteration in the physical state of yeast. A yeast spot assay demonstrated a decrease in cell viability with increasing laser irradiation dose. The results indicate a correlation between changes in electrical properties, cell viability, and the efficacy of 405 nm laser-induced inactivation. Impedance spectroscopy is shown to be an efficient, non-destructive, label-free method for monitoring changes in cell viability in photobiological effect studies. The development of impedance spectroscopy-based real-time studies in photoinactivation holds promise for advancing our understanding of light-cell interactions in medical applications.

Amyloid-β Oligomer-Induced Electrophysiological Mechanisms and Electrical Impedance Changes in Neurons

Amyloid plays a critical role in the pathogenesis of Alzheimer's disease (AD) and can aggregate to form oligomers and fibrils in the brain. There is increasing evidence that highly toxic amyloid-β oligomers (AβOs) lead to tau protein aggregation, hyperphosphorylation, neuroinflammation, neuronal loss, synaptic loss, and dysfunction. Although the effects of AβOs on neurons have been investigated using conventional biochemical experiments, there are no established criteria for electrical evaluation. To this end, we explored electrophysiological changes in mouse hippocampal neurons (HT22) following exposure to AβOs and/or naringenin (Nar, a flavonoid compound) using electrical impedance spectroscopy (EIS). AβO-induced HT22 showed a decreased impedance amplitude and increased phase angle, and the addition of Nar reversed these changes. The characteristic frequency was markedly increased with AβO exposure, which was also reversed by Nar. The AβOs decreased intranuclear and cytoplasmic resistance and increased nucleus resistance and extracellular capacitance. Overall, the innovative construction of the eight-element CPE-equivalent circuit model further reflects that the pseudo-capacitance of the cell membrane and cell nucleus was increased in the AβO-induced group. This study conclusively revealed that AβOs induce cytotoxic effects by disrupting the resistance characteristics of unit membranes. The results further support that EIS is an effective technique for evaluating AβO-induced neuronal damage and microscopic electrical distinctions in the sub-microscopic structure of reactive cells.

Bio-inspired microfluidics: A review

Biomicrofluidics, a subdomain of microfluidics, has been inspired by several ideas from nature. However, while the basic inspiration for the same may be drawn from the living world, the translation of all relevant essential functionalities to an artificially engineered framework does not remain trivial. Here, we review the recent progress in bio-inspired microfluidic systems via harnessing the integration of experimental and simulation tools delving into the interface of engineering and biology. Development of "on-chip" technologies as well as their multifarious applications is subsequently discussed, accompanying the relevant advancements in materials and fabrication technology. Pointers toward new directions in research, including an amalgamated fusion of data-driven modeling (such as artificial intelligence and machine learning) and physics-based paradigm, to come up with a human physiological replica on a synthetic bio-chip with due accounting of personalized features, are suggested. These are likely to facilitate physiologically replicating disease modeling on an artificially engineered biochip as well as advance drug development and screening in an expedited route with the minimization of animal and human trials.

Effective Capacitance from Equivalent Electrical Circuit as a Tool for Monitoring Non-Adherent Cell Suspensions at Low Frequencies

Analyzing the electrical double layer (EDL) in electrical impedance spectroscopy (EIS) measurement at low frequencies remains a challenging task for sensing purposes. In this work, we propose two approaches to deal with the EDL in measuring impedance for particles and non-adherent cells in an electrolytic suspension. The first approach is a simple procedure to compute a normalized electrical impedance spectrum named dispersed medium index (DMi). The second is the EIS modeling through an equivalent electric circuit based on the so-called effective capacitance (Cef), which unifies the EDL phenomena. Firstly, as an experiment under controlled conditions, we examine polymer particles of 6, 15, and 48 μm in diameter suspended in a 0.9% sodium chloride solution. Subsequently, we used K-562 cells and leukocytes suspended in a culture medium (RPMI-1640 supplemented) for a biological assay. As the main result, the DMi is a function of the particle concentration. In addition, it shows a tendency with the particle size; regardless, it is limited to a volume fraction of 0.03 × 10−4 to 58 × 10−4. The DMi is not significantly different between K-562 cells and leukocytes for most concentrations. On the other hand, the Cef exhibits high applicability to retrieve a function that describes the concentration for each particle size, the K-562 cells, and leukocytes. The Cef also shows a tendency with the particle size without limitation within the range tested, and it allows distinction between the K-562 and leukocytes in the 25 cells/µL to 400 cells/µL range. We achieved a simple method for determining an Cef by unifying the parameters of an equivalent electrical circuit from data obtained with a conventional potentiostat. This simple approach is affordable for characterizing the population of non-adherent cells suspended in a cell culture medium.

A Novel Genetic Neural Network Algorithm with Link Switches and Its Application in University Professional Course Evaluation

This study exploits a novel enhanced genetic neural network algorithm with link switches (EGA-NNLS) to model the professional university course evaluating system. Various indices should be employed to evaluate the learning effect of a professional course comprehensively and objectively, and the traditional artificial evaluation methods cannot achieve this goal. The presented data-driven modeling method, EGA-NNLS, combines a neural network with link switches (NN-LS) with an enhanced genetic algorithm (EGA) and the Levenberg-Marquardt (LM) algorithm. It employs an optimized network structure combined with EGA and NN-LS to learn the relationships between the system's input and output from historical data and uses the network's gradient information via the LM algorithm. Compared with the traditional backpropagation neural network (BPNN), EGA-NNLS achieves a faster convergence speed and higher evaluation precision. In order to verify the efficiency of EGA-NNLS, it is applied to a collection of experimental data for modeling the professional university course evaluating system.