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Rehabilitation Computing in Electronic Computing
Published in Parveen Berwal, Jagjit Singh Dhatterwal, Kuldeep Singh Kaswan, Shashi Kant, Computer Applications in Engineering and Management, 2022
Parveen Berwal, Jagjit Singh Dhatterwal, Kuldeep Singh Kaswan, Shashi Kant
The patch-clamp methodology has been successfully used to study cellular ion channels. The practice is accomplished of sensing streams flowing in/out of the cell concluded a single ion network at peak resolution. The dysfunction of ion channels has now been shown to be the cause of a variety of diseases. The patch-clamp system can be used to study the operation of different ion channels under various physical and chemical stimulations, as well as cell communications, and these experiments can help one better understand the fundamentals of cells. Patch clamping involves isolating a patch of membranes from the extracellular environment with a glass Pasteur pipette to record the current running into the region. Glass micropipettes with a tip diameter of 1–2 m are created by heating and pulling small glass capillaries. After that, the capillary tubes are backfilled with an electrical conductor and rubbed against a surface of cells. A soft suction is applied to the pipette’s backend to increase the sealing state. In the enzyme immobilization setup, there are different attributes: monitoring electrodes within the pipette and a buffer solution in the bath solution, as shown in A resistive element seal between both the crystal and the membrane patch is done to avoid single cell membrane current flow of the order of a few Pico Amperes. The increased resistance seal decreases current flow between the metal conductors, finishes the membrane patch’s electrical separation, and lowers recording current noise. The seal is known as a giga-seal because its thermal conductivity is in the gig ohm range.
Microfluidics in Neuroscience
Published in Tuhin S. Santra, Microfluidics and Bio-MEMS, 2020
Pallavi Gupta, Nandhini Balasubramaniam, Kiran Kaladharan, Fan-Gang Tseng, Moeto Nagai, Hwan-You Chang, Tuhin S. Santra
Electrophysiology is the study of the electrical properties (electric current and membrane potential) of cells and tissues, ranging from single-ion channel properties to those of whole organs. Electrophysiology using MEAs depends on the distance, strength, and stability of the interfacial contact between the electrogenic cells and an electrode. The patch-clamp technique is a classical tool for studying single- or multiple-ion channels of cells. In a traditional patch-clamp technique, a fire-polished glass pipette with a tip diameter in the range of 1–2 μm is pressed into a cell membrane using a micromanipulator. To electrically isolate cells, the membrane is sealed to the pipette with suction, enabling the recording of even single-channel ion fluxes. Although this process has a high resolution, it has very low efficiency and is time consuming.
Silicon-Based Nanoscale Probes for Biological Cells
Published in Klaus D. Sattler, st Century Nanoscience – A Handbook, 2020
Youjin Lee, Andrew W.Phillips, Bozhi Tian
The patch-clamp technique is a traditional electrophysiology tool used to record intracellular electrical currents. In this technique, a thin glass micropipette with a recording microelectrode inside is filled with an electrolyte and inserted into a cell. A reference electrode is inserted into the solution surrounding the cell and ionic currents are recorded between the electrodes. Even though the technique can yield high spatial resolution—up to single ion channel recording—with high signal-to-noise ratio, it has nontrivial setbacks (Sakmann and Neher 1984). Decreasing the size of the micropipette is crucial for increasing the spatial resolution. However, small micropipettes will give high impedance between the micropipette and the cell interior, thus decreasing the temporal resolution as well as the signal-to-noise ratio (Prohaska et al. 1986). Another set of techniques used for probing cellular electrical activities include voltage- and calcium-sensitive dyes, which display high temporal and spatial resolution (Grinvald and Hildesheim 2004; Rochefort, Jia, and Konnerth 2008). The dye-based techniques however, suffer from challenges such as photobleaching, cytotoxicity from the dye, and differential dye loading efficiency.
Model-guided concurrent data assimilation for calibrating cardiac ion-channel kinetics
Published in IISE Transactions on Healthcare Systems Engineering, 2023
Haedong Kim, Hui Yang, Andrew R. Ednie, Eric S. Bennett
Repolarization is a complex process that involves various Kv isoforms. It is critical to understand the unique properties and functional roles of each Kv to investigate pathological mechanisms of diseased cardiomyocytes that contribute to fatal heart diseases. However, current laboratory techniques, such as whole-cell patch-clamp recording, are not able to measure individual activities of Kv isoforms reliably that activate, inactivate, and close at overlapping times during recordings, except through the attempt to remove Kv isoform activity through less-than-fully-specific pharmacological intervention. Thus, only the sum of the different Kv isoform activities can be measured as a single current trace, IKsum. Hence, it is necessary to decompose IKsum into individual K+ currents and estimate their channel activity via data assimilation. This paper presents a subject-specific concurrent data assimilation method for learning Kv activities using multiple IKsum recordings simultaneously for each cell. A case study is provided using our in-vitro experimental data of mouse cardiomyocyte IK in control conditions (WT) and under conditions of reduced complex N-glycosylation (MGAT1KO). We evaluate the calibration results using an adjusted measure for nonlinear models that preserves the interpretability of the classical based on the variance decomposition for linear models. Experimental results show the proposed method explains more than 90% of variances by calibrated models in most cases (WT: MGAT1KO: ).
Network dilution and asymmetry in an efficient brain
Published in Philosophical Magazine, 2020
Marco Leonetti, Viola Folli, Edoardo Milanetti, Giancarlo Ruocco, Giorgio Gosti
The human brain contains billions of neurons connected with more than a hundred trillion synapses which build countless structures forming anatomically distinguishable regions. Brain imaging allows us to observe the complex dynamical patterns of neural activation which occur while mental processes are executed. In this complex dynamical system perspective [1–6], each cell determines his activation state depending on its internal state, and on the activation state of the cells to which it is connected through synapses. Consequently, the single neuron activities collectively give rise to dynamical patterns. These dynamical patterns are universally acknowledged to be responsible for how the brain functions [3]. Several models [7,8] disregard the collective nature of brain functions, and give quantitative descriptions of single neuron behaviour based on patch-clamp voltage measurements [9]. However, many critical functions such as memory, pattern recognition and mathematical operations are carried out by one (or more than one) circuit rather than individual neurons. Even if it is still mostly unknown how the brain, or any distributed hierarchical-less computational system collective, carries out these complex functions [10,11], Hopfield developed a simplified approach to model how a circuit may store memories and associative behaviours [5,6]. This model demonstrates that discrete-time Recurrent Neural Networks (RNN) with randomly connected networks and McCulloch–Pitts neurons possess attractors (states that periodically repeat) which represent the stored memories or network stored behavioural patterns [12,13]. It is easy to demonstrate that discrete-time RNN with completely connected symmetric networks converge fast and possess many attractors [14]: unfortunately, these networks are efficient but far from a real biological system.
Predicting the cardiac toxicity of drugs using a novel multiscale exposure–response simulator
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2018
Francisco Sahli Costabal, Jiang Yao, Ellen Kuhl
We model the effect of drugs on the single-cell action potential by selectively blocking the relevant ionic currents. The fractional blockage of individual ion channels at varying drug concentrations can be measured using patch clamp electrophysiology (Crumb et al. 2016). To estimate the fractional block at arbitrary concentrations C, we can fit a Hill-type equation to the discrete data points,