amplitude-modulated-electrodeformation-to-evaluate-mechanical-fatigue

Amplitude-Modulated Electrodeformation to Evaluate Mechanical Fatigue of Biological Cells

Red blood cells (RBCs) are known for their remarkable deformability. They repeatedly undergo considerable deformation when passing through the ...

Florida Atlantic University

We present a comprehensive theoretical-experimental framework for quantitative, high-throughput study of cell biomechanics. An improved electrodeformation method has been developed by combing dielectrophoresis and amplitude shift keying, a form of amplitude modulation. This method offers a potential to fully control the magnitude and rate of deformation in cell membranes. In healthy human red blood cells, nonlinear viscoelasticity of cell membranes is obtained through variable amplitude load testing. A mathematical model to predict cellular deformations is validated using the experimental results of healthy human red blood cells subjected to various types of loading. These results demonstrate new capabilities of the electrodeformation technique and the validated mathematical model to explore the effects of different loading configurations on the cellular mechanical behavior. This gives it more advantages over existing methods and can be further developed to study the effects of strain rate and loading waveform on the mechanical properties of biological cells in health and disease.

Modeling erythrocyte electrodeformation in response to amplitude modulated electric waveforms.

This article presents the development and testing of a low-cost (<$60), portable, electrical impedance-based microflow cytometer for single-cell analysis under a controlled oxygen microenvironment. The system is based on an AD5933 impedance analyzer chip, a microfluidic chip, and an Arduino microcontroller operated by a custom Android application. A representative case study on human red blood cells (RBCs) affected by sickle cell disease is conducted to demonstrate the capability of the cytometry system. Impedance values of sickle blood samples exhibit remarkable deviations from the common reference line obtained from two normal blood samples. Such deviation is quantified by a conformity score, which allows for the measurement of intrapatient and interpatient variations of sickle cell disease. A low conformity score under oxygenated conditions or drastically different conformity scores between oxygenated and deoxygenated conditions can be used to differentiate a sickle blood sample from normal. Furthermore, an equivalent circuit model of a suspended biological cell is used to interpret the electrical impedance of single flowing RBCs. In response to hypoxia treatment, all samples, regardless of disease state, exhibit significant changes in at least one single-cell electrical property, that is, cytoplasmic resistance and membrane capacitance. The overall response to hypoxia is less in normal cells than those affected by sickle cell disease, where the change in membrane capacitance varies from -23% to seven times as compared with -17% in normal cells. The results reported in this article suggest that the developed method of testing demonstrates the potential application for a low-cost screening technique for sickle cell disease and other diseases in the field and low-resource settings. The developed system and methodology can be extended to analyze cellular response to hypoxia in other cell types.

A portable impedance microflow cytometer for measuring cellular response to hypoxia.

Sickle cell disease is characterized by painful vaso-occlusive crises, in which poorly deformable sickle cells play an important role in the complex vascular obstruction process. Existing techniques are mainly based on optical microscopy and video processing of sickle blood flow under normoxic condition, for measuring vaso-occlusion by a small fraction of dense sickle cells of intrinsic rigidity but not the vaso-occlusion by the rigid, sickled cells due to deoxygenation. Thus, these techniques are not suitable for rapid, point-of-care testing. Here, we integrate electrical impedance sensing and Polydimethylsiloxane-microvascular mimics with controlled oxygen level into a single microfluidic chip, for quantification of vaso-occlusion by rigid, sickled cells within 1 min. Electrical impedance measurements provided a label-free, real-time detection of different sickle cell flow behaviors, including steady flow, vaso-occlusion, and flow recovery in response to the deoxygenation-reoxygenation process that are validated by microscopic videos. Sensitivity of the real part and imaginary part of the impedance signals to the blood flow conditions in both natural sickle cell blood and simulants at four electrical frequencies (10, 50, 100, and 500 kHz) are compared. The results show that the sensitivity of the sensor in detection of vaso-occlusion decreases as electrical frequency increases, while the higher frequencies are preferable in measurement of steady flow behavior. Additional testing using sickle cell simulants, chemically crosslinked normal red blood cells, shows same high sensitivity in detection of vaso-occlusion as sickle cell vaso-occlusion under deoxygenation. This work enables point-of-care testing potentials in rapid, accurate detection of steady flow and sickle cell vaso-occlusion from microliter volume blood specimens. Quantification of sickle cell rheology in response to hypoxia, may provide useful indications for not only the kinetics of cell sickling, but also the altered hemodynamics as obseved at the microcirculatory level.

Rapid electrical impedance detection of sickle cell vaso-occlusion in microfluidic device.

Individuals who have suffered neurotrauma like a stroke or brachial plexus injury often experience reduced limb functionality. Soft robotic exoskeletons have been successful in assisting rehabilitative treatment and improving activities of daily life but restoring dexterity for tasks such as playing musical instruments has proven challenging. This research presents a soft robotic hand exoskeleton coupled with machine learning algorithms to aid in relearning how to play the piano by 'feeling' the difference between correct and incorrect versions of the same song. The exoskeleton features piezoresistive sensor arrays with 16 taxels integrated into each fingertip. The hand exoskeleton was created as a single unit, with polyvinyl acid (PVA) used as a stent and later dissolved to construct the internal pressure chambers for the five individually actuated digits. Ten variations of a song were produced, one that was correct and nine containing rhythmic errors. To classify these song variations, Random Forest (RF), K-Nearest Neighbor (KNN), and Artificial Neural Network (ANN) algorithms were trained with data from the 80 taxels combined from the tactile sensors in the fingertips. Feeling the differences between correct and incorrect versions of the song was done with the exoskeleton independently and while the exoskeleton was worn by a person. Results demonstrated that the ANN algorithm had the highest classification accuracy of 97.13% ± 2.00% with the human subject and 94.60% ± 1.26% without. These findings highlight the potential of the smart exoskeleton to aid disabled individuals in relearning dexterous tasks like playing musical instruments.

Darryl Dieujuste

Department of Ocean and Mechanical Engineering

Florida Atlantic University

Amplitude-Modulated Electrodeformation to Evaluate Mechanical Fatigue of Biological Cells

Darryl Dieujuste

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Ocean and Mechanical Engineering

Florida Atlantic University

Amplitude-Modulated Electrodeformation to Evaluate Mechanical Fatigue of Biological Cells

Department of Ocean and Mechanical Engineering