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Bioengineering
  • Article
  • Open Access

10 June 2019

A Multidisciplinary Approach toward High Throughput Label-Free Cytotoxicity Monitoring of Superparamagnetic Iron Oxide Nanoparticles

,
and
1
Biologically Inspired Sensors and Actuators Laboratory, Lassonde School of Engineering, York University, Ontario, Toronto, ON M3J 1P3, Canada
2
Department of Biology, York University, Toronto, ON M3J 1P3, Canada
3
Department of Psychology, York University, Toronto, ON M3J 1P3, Canada
4
Department of Electrical Engineering and Computer Science, York University, Toronto, ON M3J 1P3, Canada
This article belongs to the Collection Nanoparticles for Therapeutic and Diagnostic Applications

Abstract

This paper focuses on cytotoxicity examination of superparamagnetic iron oxide nanoparticles (SPIONs) using different methods, including impedance spectroscopy. Recent advances of SPIONs for clinical and research applications have triggered the need to understand their effects in cells. Despite the great advances in adapting various biological and chemical methods to assess in-vitro toxicity of SPIONs, less attention has been paid on the development of a high throughput label-free screening platform to study the interaction between the cells and nanoparticles including SPIONs. In this paper, we have taken the first step toward this goal by proposing a label-free impedimetric method for monitoring living cells treated with SPIONs. We demonstrate the effect of SPIONs on the adhesion, growth, proliferation, and viability of neuroblastoma 2A (N2a) cells using impedance spectroscopy as a label-free method, along with other standard microscopic and cell viability testing methods as control methods. Our results have shown a decreased viability of the cells as the concentration of SPIONs increases with percentages of 59%, 47%, and 40% for 100 µg/mL (C4), 200 µg/mL (C5), 300 µg/mL (C6), respectively. Although all SPIONs concentrations have allowed the growth of cells within 72 h, C4, C5, and C6 showed slower growth compared to the control (C1). The growth and proliferation of N2a cells are faster in the absence or low concentration of SPIONS. The percent coefficient of variation (% CV) was used to compare cell concentrations obtained by TBDE assay and a Scepter cell counter. Results also showed that the lower the SPIONs concentration, the lower the impedance is expected to be in the sensing electrodes without the cells. Meanwhile, the variation of surface area (∆S) was affected by the concentration of SPIONs. It was observed that the double layer capacitance was almost constant because of the higher attachment of cells, the lower surface area coated by SPIONs. In conclusion, impedance changes of electrodes exposed to the mixture of cells and SPIONs offer a wide dynamic range (>1 MΩ using Electric Cell-substrate Impedance electrodes) suitable for cytotoxicity studies. Based on impedance based, viability testing and microscopic methods’ results, SPIONs concentrations higher than 100 ug/mL and 300 ug/mL cause minor and major effects, respectively. We propose that a high throughput impedance-based label-free platform provides great advantages for studying SPIONs in a cell-based context, opening a window of opportunity to design and test the next generation of SPIONs with reduced toxicity for biomedical or medical applications.

1. Introduction

Superparamagnetic Iron Oxide Nanoparticles (SPIONs) have attracted the attention of researchers for clinical and research purposes due to their structural and magnetic properties that make them suitable for drug delivery, disease diagnostics and treatment purposes [,]. SPIONs are chemically made up of magnetite (Fe3O4) and maghemite (γ-Fe2O3) []. By applying a magnetic field, SPIONs are directed as nanoscale carriers to a target organ in the body. For instance, several studies have shown that SPIONs can cross the Blood Brain Barrier (BBB) [,] and deliver the drug into the brain [,]. In these studies, the uptake of SPIONs by the astrocytes [] can be used as an indicator of nanoparticle (NP) delivery through BBB. Other studies have shown that SPIONs lower than a certain concentration level are not toxic compared to other higher saturation magnetic NPs [,,]. The Food and Drug Administration’s (FDA) approval [] of SPIONs as MRI contrast agents has created an intense interest in promoting the use of these nanomaterials in humans [] for various clinical applications, including diagnostic and treatment of brain diseases over the last decade [,].
Despite significant advances of SPIONs for various life science applications, many research studies should still be conducted to enhance our understanding of the effects of SPIONs with different concentrations on cellular activities. It is in this direction that this paper progresses, specifically by focusing on the interaction of SPIONs and brain cells using various methods, including impedance spectroscopy.
Figure 1 illustrates the proposed in-vitro method in this paper to mimic the uptake of SPIONs on brain cells. This method offers great advantages for studying the interaction of SPIONs and the brain cells as described and demonstrated in the next sections. The remainder of this section provides a comprehensive review of the literature to explain the advantages of SPIONs for neuronal studies, and other applications in Section 1.1, followed up by Section 1.2 that briefly reviews the in-vitro studies of the effects of NPs on cells.
Figure 1. Schematic representation of the interaction of the brain cells with SPIONs when studied in in-vitro using an impedance-based assay.

1.1. SPIONs Applications

SPIONs have demonstrated great advantages for various life science applications including non-invasive Magnetic Resonance Imaging (MRI) [], diagnosis of ailment, drug delivery and development [], thermotherapy [], biological separation [], cell transfection [], immunoassays [], gene delivery [], tissue engineering [], and cell tracking in cancer and its treatments []. Some important SPIONs applications are briefly put forward as follows.
  • MRI Contrast Agent: MRI is used to visualize and track a diseased portion of the brain. The strength of the signal is influenced by the two-relaxation times of water protons, the longitudinal (TL) and transverse (TT) [,]. For the image refinement, contrast agents are utilized to decrease TL and TT relaxation times. The SPIONs act as negative contrast agents, producing a negative signal on TT weighted images and enhancing TT contrast [].
  • Tumor Diagnostics and Therapy: Functionalized SPIONs can play an essential role in the delivery of therapeutic components and subsequently for initiating tumor cell death []. A biocompatible coating on SPIONs provides suitable functional groups for conjugating with tumor cells [,]. For instance, SPIONs can be attached to the anti-IL-1β monoclonal antibody to be used for MRI diagnoses and targeted therapy by neutralizing IL-1β which is overexpressed in the epileptogenic area of an acute rat model with temporal lobe epilepsy [], a disease in the brain associated with inflammation [].
  • Thermotherapy: To implement a hyperthermia treatment, SPIONs can be introduced in the body through a magnetic delivery system or a local injection to the affected area []. SPIONs can vibrate and produce heat in an interchanging magnetic field [,]. The generated heat can be used for thermotherapy purposes.
  • Crossing BBB: As previously mentioned, recent studies have reported that SPIONs can enter the brain without causing damage to the blood-brain barrier []. To date, many types of research have been conducted to understand the BBB mechanisms and enhance the BBB permeability using functionalized SPIONs. Among these efforts is an optimized in-vitro BBB model, which was recently being reported using mouse brain endothelial cells and astrocytes [,]. Also, experimental data demonstrated how one could modify SPIONs to deliver drugs to the brain to more effectively treat a wide range of neurological disorders [].
  • Drug Delivery: SPIONs are widely used because of their larger surface to mass ratio [] compared to other NPs, their quantum properties [] and their ability to absorb [] and carry other compounds. The aims for such NP entrapment of drugs are either enhanced delivery to or uptake by, target cells and a reduction in the toxicity of the free drug to non-target organs. Both situations will increase the ratio between the doses resulting in therapeutic efficacy and toxicity to other organ systems. For these reasons, the creation of long-lived and target-specific NPs and accurate toxicity studies should be performed to increase the advantages of these particles for the applications mentioned earlier []. It is noteworthy that SPIONs are not stable under physiological conditions due to the reduction of electrostatic repulsion, which causes NP aggregation. To re-disperse SPIONs in biological media, further surface modifications are applied in particular on the commercially available SPIONs [].

1.2. Effects of NPs on Cells: In-Vitro Studies

To date, many papers have reported the advantage of NPs for drug delivery purposes using in-vivo animal models [,]. In comparison with in-vivo studies of NPs, less attention has been paid to studying the effect of NPs using in-vitro cell culture models. In general, even though in-vivo animal model studies offer exceptional advantages for testing NPs or other drugs in human-like fully functional organs, in-vitro cell culture models can also provide unique benefits for various fundamental biological and clinical studies. These advantages include higher environmental control, less variability, low complexity and higher repeatability []. It is noteworthy to mention that N2a cells have been used widely for in-vitro neuroscience studies due to their capacity to differentiate [] and respond to electrophysiological stimulation []. In this paper, N2a cells were used as an in-vitro cell culture model.

1.2.1. Fundamental Effects

In in-vitro models, NPs including SPIONs can directly be added to the cell culture, and they interact with the culture medium [], aggregate in the intercellular spaces, attach to the cell membrane [] and affect intracellular parts of the cell []. Indeed, the culture medium can change the properties of NPs by forming a protein coat covering the entire NP []. This may increase the adhesion properties of NPs for the attachment to the cell membrane. NPs’ distinctive physicochemical properties with increased responsiveness and propensity to pass through the cell membrane and other biological barriers cause stress and induce cytotoxicity []. Herein, the major effects of NPs on cells are highlighted.
  • Effect on cell membrane: All types of NPs including SPIONs can be assimilated into the cell via different processes and all these types passe through the protective barrier of the cell—the cell membrane. As NPs make their way through the cell membrane, they affect the major components of the membrane, the proteins [,] and the lipid bilayer [].
  • Effect on Lysosomes: A study using silica (SiO2) NPs on human cervix carcinoma (HeLa) cells, had shown that NPs disrupt normal activities of the lysosomes by causing damage in their cargo delivery via autophagosomes. Although the autophagy-mediated protein turnover and degradation of internalized epidermal growth factor were affected, this did not induce cell death [].
  • Effect on cytoplasmic organelles: Experimental investigation has shown evidence that NPs affect cytoplasmic organelles like the mitochondria [] and nucleus []. Another study had shown that even if using gold nanoparticles (GNPs) does not cause accumulation within the mitochondria, NPs close to the organelle could still enhance damage due to the delocalization of photoelectrons from the cytosol. Furthermore, the presence of GNPs in the cytosol increases the energy deposition in the mitochondrial volume more than the presence of GNPs within the nuclear volume [].
  • Effects on the cell activities: The effect of GNPs on cell differentiation and maturation has been highlighted in another study. It has been observed that the cells developed longer neuronal outgrowth in the presence of GNPs [,].
  • Other effects: The exposure of the cell to NPs brings about harmful effects such as damage mitochondrial function, inflammation, the formation of apoptotic bodies, membrane leakage of lactate dehydrogenase, reactive oxygen species (ROS) production, increase in micronuclei, and chromosome condensation []. In such cytotoxicity studies, there are various indicators such as micronuclei that are an indicator of gross chromosomal damage that is used to measure genotoxicity.
Despite significant advances in the studying of NPs in different types of cells, still, the effects of many kinds of NPs on various parts of cells or different types of cells have not been studied. In this paper, we only focus on exploring the effects of SPIONs on N2a using three cellular level indicators, namely; cell viability, morphology, and cell adhesion.

1.2.2. In-vitro Toxicity Assays

As previously mentioned, NPs can affect many different parts of the cell. Thus, various conventional toxicity assays are required to measure the damage caused by NPs. As per the literature, these assays include 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromidefor (MTT) assay, cell metabolic activity assay (WST-1), Cell Proliferation 5-Bromo-2´-Deoxyuridine (BrdU) Analysis [,], lactate dehydrogenase (LDH) leakage, fluorescent propidium iodide (PI), [3H] thymidine, Clonogenic assays, Electron paramagnetic resonance (EPR), Lipid peroxidation Assay, Enzyme-linked immunosorbent assay (ELISA) and Trypan blue dye exclusion (TBDE) test [].
Most recently, various new sensing methods are being used in toxicity studies. Among these new methods, Fritzsche et al. reported a cell-based fluorometric sensor system [,]. This system uses fluorescence data, which is generated by connecting a multi-well culture plate to a fluorescence spectrometer. With software, concentration curves were further analyzed. These curves are also used to indicate the concentration of the toxicant. In another effort, impedance spectroscopy [,] has opened the possibility of a faster, real-time, high-throughput acquisition of results. For instance, an Electric cell-substrate impedance sensing (ECIS) device that was used to monitor mammalian cell activities under the presence of toxicant. This device was connected to a PDMS perfusion system and impedance spectroscopy system []. Also, the impedance-based method was used to investigate the change in the activity of macrophage cell line J774, epithelial cell line MDCK and fibroblasts []. In this direction, another effort was made by Zhu et al., who presented the lateral flow immunoassay (LFIA) to determine toxicity at the genetic level []. In another attempt, a multichannel dissolved oxygen sensor consisting of a 96-well electrodes biosensor was introduced by the group of Sadik et al. to detect toxicity. Their measurement setup was used for monitoring the amount of oxygen used by the cell []. Also, the paper authored by Özel et al. provided information on using electrochemical approaches in monitoring the effect of NPs [].
The first section presents a comprehensive review of several related papers of literature on the different SPIONs applications and effects of NPs on cells in-vitro studies. The next section emphasizes related works on SPIONs’ cytotoxicity studies and high throughput impedance-based cellular analysis. The third section gives a clear understanding of the materials used in this study and explains the methods that had been performed to gather the data. Section 4 displays the results in the form of graphs, figures, and tables. Each result is explicitly discussed, including the integration impedance spectroscopy results and equivalent circuit model. Further discussion can be seen in Section 5 where economical and time assessments as well as a high throughput analysis device for the future were highlighted. Finally, the last section establishes conclusions based on the results.

3. Materials and Methods

This section presents the materials and methods used in the study. It also describes the research process and the details of the methods used in an operational manner.

3.1. Materials

3.1.1. Organism

The Neuroblastoma 2a cells (Neuro 2a or N2a cells) are a fast-growing mouse neuroblastoma cell line derived from an albino mouse strain []. This cell line was purchased from ATCC®. The maintenance, storage, and manipulation of the cell line used in this study were performed at the Medical Devices Laboratory at the Bergeron Building, York University.

3.1.2. Chemicals

Most of the chemicals and reagents, including DMEM, FBS, PS, PBS, and trypan blue dye). Ethanol (Commercial ALC.), fetal bovine serum (FBS) (Life Technologies) and water (ultrapure type I) were purchased from Sigma-Aldrich (Oakville, Canada). The spherical shape SPIONs were purchased from Skyspring Nanomaterials, Inc (Houston TX, USA). The average size of SPIONs used in this study was ~10–15 nm. Characterization of SPIONs in terms of XRD pattern, SEM image and magnetic properties is available from reference [].
Solutions and Media for Cell Culture
Subculturing the cell was performed using phosphate buffered saline (PBS) (Sigma-Aldrich Canada Co., Toronto, Canada), containing 0.9% Sodium chloride, 99% Water, 0.0144% Potassium dihydrogenorthophosphate, 0.0795% Sodium monohydrogen phosphate, heptahydrate, pH 7.2, sterile-filtered, trypsin-EDTA (Sigma-Aldrich Canada Co.) containing 0.05% trypsin, 0.02% EDTA (1×) in D-PBS (PAA). Meanwhile, Dulbecco’s Modified Eagle Medium (DMEM), (Sigma Life Science, Darmstadt, Germany), with 4500 mg/L glucose, L-glutamine, and sodium bicarbonate, without sodium pyruvate, liquid, sterile-filtered, 1% Antibiotics—penicillin/streptomycin (Sigma) made up of 10,000 units’ penicillin and 10 mg streptomycin/mL, sterile-filtered, Bio-Reagent and 10% Fetal Bovine Serum (Sigma) were used to prepare the complete culture medium (CCM).

3.1.3. Consumables

Most of the non-chemical consumables as listed below were purchased from Fisher Scientific (Pittsburgh, PA, USA) and the electrodes for impedance measurements were purchased from Applied Biophysics Inc. (New York, NY, USA).
Consumables for Biological Sample Preparation and Test
Biological Sample Preparation requires precision and careful handling. This entails use of different materials such as Sarstedt Serological pipettes (Sarstedt AG & Co. KG, Nümbrecht, Germany), Culture dishes TC-Schale (Standard Sarstedt AG & Co. KG), 12 and 6 well Culture Plates (Sarstedt AG & Co. KG), Conical centrifuge tubes (Thermo Scientific, Waltham, MA, USA), Petri dish (Sarstedt AG & Co. KG), Universal Fit pipette tips and microtubes (Sarstedt, Corning Inc., Newton, NC, USA) Cell counter 40 μm sensor (Scepter™ 2.0, Millipore Sigma, Burlington, MA, USA).
Consumable for Impedance Analysis
Recording and analysis of impedance were made possible by using two different electrode arrays. The Electrode Array (type 1) ECIS, PC (Clear polycarbonate substrate) 1E, Diameter of electrode (central hole), 250 μm and Electrode Array (type 2) ECIS, PCB (Non transparent Printed Circuit Board) IE Diameter of electrode (central hole), 250 μm of 0.049 mm2 were purchased at Applied Biophysics Inc, NY, USA.

3.1.4. Equipment

All equipment used in this project for biological sample preparation and analysis, impedance measurement and analysis and microscopic analysis are listed below.
Required Equipment for Biological Sample Preparation and Test
The N2a cells were incubated in a Heracell 150i incubator (Thermo Fisher Scientific). Chemicals were prepared and maintained in Forma refrigerator (Thermo Scientific) and stored at Forma 900 series freezer. All cell culture techniques, including preparation and aliquoting, of the solutions, were performed in a laminar flow unit 1300 series A2 (Thermo Scientific). The HiFlow, F19917-0250 Vacuum Aspirator Collection System (SP Scienceware), Isotemp Digital 2320 Water Bath (Fisher Scientific), and Sorvall ST 8 Lab Centrifuge (Thermo Scientific) were also used. The Fisherbrand™ Analog Vortex Mixer (Fisher Scientific) was used during the preparation cell-dye mixture of TBDE Assay. Equally important equipment used during the preparation was Quintix® Analytical Balance (Sartorius), Hanna Checker® pH meter (Sigma Aldrich). Sceptre™ 2.0 Handheld Cell Counter (Millipore Sigma) was used during the cell counting.
Required Equipment and Accessories for Microscopic Analysis
Images were captured with the used of Fisherbrand™ Inverted and phase contract Microscope (Fishers Scientific) with an attached Education™ Motic D-Moticam 1080 Digital HDMI camera (Fishers Scientific). BLAUBRAND® Neubauer Hemocytometer (Millipore Sigma) was used during the manual counting and visualization of live and dead cells.
Required Equipment for Impedance Analysis
Autolab PGSTAT101, FRA32M electrochemical impedance spectroscopy (EIS) module (Metrohm, Herichaut, Switzerland) was the primary equipment for the impedance analysis.

3.1.5. Software

The following software was utilized in obtaining data and for analysis purposes. The Scepter™ 2.0 Software Pro User Interface (Millipore Sigma) was used for cell concentration and volume determination. Concurrently, Motic 2.0 software (Fishers Scientific) was used to record the images. NOVA 2.0 software (Metrohm) was used to record and analyze impedance. Excel (Microsoft) had been used for displaying and analyzing the data.

3.2. Methods

In this work, the cells were cultured with different concentration of SPIONs (0, 25, 50, 100, 200 and 300 µg/mL) in the traditional Petri dish and in the ECIS electrode array as seen in Figure 2. The cell viability, cell morphology analysis, and the impedance-based cell–surface attachment in the presence of SPIONs are measured using various methods. The details of the measurement results are shown in the next section.
Figure 2. Scheme of proposed experimental setup including an array of 8 sensors incorporated with cell culture wells. These electrodes are connected to a computer through an impedance readout system. The cells are loaded by a standard pipette and observed under a microscope.

3.2.1. Sample Preparation and Biological Test

In this subsection, the protocols related to the preparation of samples including biological cells, SPIONs and their related biological assays were put forward.
Preparation of SPIONs with Different Concentration
After thorough calculations, the 300 µg/mL, 200 µg/mL, 100 µg/mL, 50 µg/mL, and 25 µg/mL concentrations of SPIONs were prepared by weighing 6, 4, 2, 1, 0.5 mg of SPIONs respectively using the Sartorius Quintix® and dissolved in the cell culture medium (CCM) to reach a total volume of 20 mL of the mixture. Then, SPION solutions were transferred into a conical tube containing a small amount of the CCM. A vortex mixer with a dimension of 20.3 × 14 × 12.2 cm was set at the speed knob 9 with a speed of 3200 rcf to disperse and dissolve the SPIONs for 15 minutes. After that, CCM was added to reach the desired volume used for the test.
Cell Culture and Maintenance
N2a cells were grown in complete culture medium (CCM) containing Dulbecco’s Modified Eagle’s Media (DMEM) supplemented with 10% Fetal Bovine Serum (FBS) and 1% antibiotic solution Penicillin-Streptomycin (PS). The cells were maintained in a Heracell CO2 incubator with 5% CO2/37 °C temperature.
As a part of maintenance, the cells were passaged twice a week. Once 90–100% confluency was reached, the cells were washed twice with 5 mL pre-warmed PBS, treated with 1 mL pre-warmed trypsin-EDTA and incubated for 1–5 min for the cells to detach from the substrate. To ensure the detachment, the cells were viewed under the microscope. 1 mL of CCM was added and transferred to a 15 mL conical centrifuge tube containing 1 mL of CCM. The mixture was put in the centrifuge with a speed of 2500 rpm in 2 min. Afterwards, the supernatant was removed, and the cells were resuspended with pre-warmed CCM in a culture Petri dish.
Cell Concentration Preparation and Inoculation
After counting the cells using hemocytometer, the concentration of 2.5 × 105 cells/mL was prepared by diluting N2a cells with CCM and SPIONs mixture. The cells were seeded in both a non-transparent (PCB model) and transparent (PC model) 8-well ECIS array. It is noteworthy that a single concentration of cell was prepared and used for all the tests.
Preparation for TBDE Test Mixture
Trypan Blue Dye Exclusion (TBDE) was used to determine the number of alive and dead cells after 72 h of exposure into the different concentrations of SPIONs. When the cell is viable, its membrane does not allow penetration of the dye leaving the cells to appear rounded, clear and shiny under the microscope, which distinguishes it from a dead cell that enables penetration of the blue dye. A 100 µL of the cell samples were diluted and gently mixed with an equal volume of trypan blue in a microtube, and it was set aside in room temperature for 3–5 min.
Cell Counting and Cell Viability Test
After 72 h cell culture, the cells were collected using the standard trypsinization method. A randomized, double-blind method was carried out for the preparation of the dilution of the trypan blue dye and cell suspension to avoid bias. Each Eppendorf tube was labelled and covered with tape. Three biological replicates were prepared for every concentration. BLAUBRAND® Neubauer Hemocytometer (Millipore Sigma) was used to count the number of dead and live cells. The coverslip was slightly moistened with ultrapure water and slid it into the hemocytometer, gently avoiding the formation of bubbles. The mixture of cells was loaded by 10 µL under the coverslip. The hemocytometer was placed under the inverted microscope using a 10× objective lens. The number of live (unstained cells) and dead (stained) cells were counted in all the five areas with 16 squares.
The Scepter™ 2.0 Handheld Cell Counter (Millipore Sigma) was also used to measure the concentration of cells. A cell suspension diluted with PBS reached a total volume of 100 µL. The mixture was put in a 2.0 mL microcentrifuge tube. When using the Scepter cell counter, a 40 µm sensor was attached and submerged into the mixture. After a 50 μL sample was drawn into the channels of the sensor, the cell concentration was displayed on the screen, and the files were transferred into the computer for analysis.

3.2.2. Microscopic Methods

An inverted microscope equipped with motic 2.0 camera and various objectives (e.g., 4×, 10× and 20×) was used to capture microscopic images in eight different times. These microscopic images were used to monitor cellular morphological changes and likely their adhesion, growth, and differentiation, in the presence of different concentrations of SPIONs.

3.2.3. Electrical Methods

The Principle of Impedance Spectroscopy Technique for Cellular Analysis
Impedance spectroscopy is a technique that measures the electrical impedance between two close electrodes exposed to the chemical or biological materials. Impedance is a combination of resistive and capacitive properties of the material. The equivalent circuit of the electrode exposed to the cells in culture can be represented with the schematic shown in Figure 3.
Figure 3. Principle of impedance measurement: (a) schematic of electrode and its equivalent circuit, (b) the sine wave voltage and current signals and (c) the impedance frequency response of electrode.
The magnitude of impedance between the electrodes can be represented by Equation (1).
| Z | = ( R 1 + R 2 ) 2 + ( ω C 1 R 2 R 1 ) 2 1 + ( ω C 1 R 1 ) 2
where R1 and C represent the resistance and capacitance properties of cells attached to the electrodes, respectively. Also, R2 represents the resistance of connectors as well as medium. f is the frequency of sine shape electrical voltage applied to the sample and resulted in an electrical current with the same frequency (see Figure 3b). f is equal to the inverse of the time T. Indeed; the impedance is equal to the magnitude of VMAX/IMAX where both VMAX and IMAX are the amplitude of electrical voltage and current signals as seen in Figure 3. As seen in Figure 3c, depending on the type of medium and biological material, the equivalent circuit can be a simple resistor or capacitor. However, the equivalent impedance magnitude is very similar to the green curves shown in Figure 3c so that by increasing the impedance, the curve 1 moves to curve 2 and then 3.
In other words, the attachment and confluence of cells on electrodes and in between the electrodes result in higher impedance. It is noteworthy that φ and τ are the time and phase differences respectively, as seen in Figure 3b so that φ = 2πτ/T = 2πfτ. In this project, we only use the magnitude of impedance. Therefore, the phase differences are not taken in our calculations.
Impedance-Based Cellular Analysis
The cell attachment and growth above the electrodes can be monitored by measuring the impedance in between the electrodes [,,,,,,,,,,,,,,,,,,]. The attachment of cells above electrodes can increase the dielectric properties and decrease the conductivity; therefore, the amount of impedance in all frequencies is increased as seen in Figure 4a. This figure shows the increase of impedance of electrodes underneath of cells in culture over time.
Figure 4. Illustration of (a) multi-curves impedance spectroscopy results and (b) the covered surface area S.
Maximum Surface Area
As the first impedance analysis method, we use the maximum variation of impedance as a healthy factor of cells in the presence of SPIONs. As seen in Figure 4b, the surface area S represents the maximum change and is calculated by Equation (2)
S = f MIN f MAX ( Z ( f ) MAX Z ( f ) MIN ) · Δ f f MAX f MIN
By knowing ∆f is the minimum frequency change and fMAX–fMIN refers to the range of scanned frequencies, therefore (fMAX–fMIN)/∆f is equal to the number (N) of the different frequencies where the impedance is measured. In other words, S can be obtained from the following equation.
S = 1 N ( Z ( f ) MAX Z ( f ) MIN ) N
As an example, Table 3 shows the parametric impedances measured in different frequencies and times. It is assumed that the cells are mixed with an arbitrary concentration of SPIONs. The maximum and minimum values of impedances are obtained and used to calculate the impedance change ∆Z = Z(f)MAX−Z(f)MIN in different times and frequencies as shown in the table. As a result, a column of various ∆Z is obtained. Based on Equation (3), the average of all numbers in this column is equal to S, and consequently, it shows the maximum variation of impedance.
Table 3. Impedance measurement in a range of frequencies (f1–fN) at different times (T1–T8).
As previously mentioned, S is equal to the average of ZMAX−ZMIN in various frequencies. In the next section, we also obtained the variance and standard deviation of ZMAX−ZMIN. Additionally, one may argue the normalized values of S can be related to the concentration of SPIONs. To show this, we also calculated the average or standard deviation of all impedances measured in each frequency (f1–fN) as seen in Table 4 that is the continuation of Table 5. In this situation, instead of ZMAX−ZMIN(f), ZMAX−ZMIN(f) /AVG(f) and STD(f) should be calculated and shown in a column. Finally, the average, variance, and STD of this column can be calculated to obtain a kind of normalized S. It is noteworthy that when using these calculation methods, we try to quantify the effect of SPIONs on cells in culture.
Table 4. Electric Equivalent Circuit for each range of frequencies.
Table 5. Continuation of Table 1, AVG and STD analysis.
Electrical Model
As per Equation (1) and as seen in Figure 3, an equivalent circuit with specific values of R1, C and R2 can be fitted with the impedances measured in each time (T1–T8) in a range of frequency, in a specific value of SPIONs. In this method, a software called NOVA 2.0 is used to find the optimum values of an equivalent circuit for each range of frequencies. In this method, various values of C, R1, and R2 for various concentrations of SPIONs were obtained at different times to study the effect of SPIONs on the cell culture over time.
Impedance Measurement Assay
Using Metrohm Autolab, the impedance spectroscopy of the eight wells were measured over different times (0, 2, 4, 6, 8, 24, 48 and 72 h). The impedance was monitored using a frequency ranging from 0.1 Hertz (Hz) to 100,000Hz with alternating current (AC) 100 mV voltage. The electrode array was interconnected into the impedance system using copper wires. The impedance measurement results were saved into Excel files for further analysis and display.
Before loading the ECIS array with cells, it was cleaned with PBS, rinsed with ultrapure water and electrodes were pre-conditioned by flooding each well with 200 µL of cysteine solution for 10 min and equilibrate with DMEM. In some circumstances, the electrodes were also further cleaned and treated in an oxygen plasma for 60 s.
After calibration, a monodisperse 2.5 × 105 cells/ml concentration of cell was inoculated separately in each of the six wells. During the inoculation, the cell suspensions were agitated to prevent settling of cells from the bottom of the tube. Meanwhile, the remaining wells were filled with the CCM and different concentrations of SPIONs without cells. After each test, the ECIS device was put back in the incubator.
In this section, the details of materials and methods were elaborated. The main methods, including biological, microscopic and impedance methods, were used to study the effect of SPIONs on the cells. These methods applied to a large number of samples as demonstrated and discussed in the next section. This study takes us a step closer to assessing the need for high throughput cellular analysis for various applications for toxicity studies.

4. Results and Discussions

In this section, the experimental results related to biological, microscopic and impedance methods are separately demonstrated and discussed in Section 4.1, Section 4.2 and Section 4.3 as summarized below.
  • Biological method: The cell viability tests were performed using the trypan blue exclusion assay. This technique was used to count the number of viable cells after 72 h (T8) of exposure.
  • Morphological method: The microscopic images of the N2a cells were captured to compare the treated and untreated cells. The treated cells were the cells mixed with SPIONs with different concentrations (C2–C6). The N2a cells were cultured in an incubator.
  • Electrical method: The attachment of cells and SPIONs above electrodes can change the impedance as described in Section 3. The impedance spectroscopy of cells in control (C1) and with the presence of SPIONs (C2–C6) are measured in different times (T1–T8) by hypothesizing that the effect of SPIONs on cells can be tracked using the recorded impedances.
Two series of cell culture experiments were performed using PC and PCB electrode arrays, as mentioned in Section 3. Each set of experiments includes three different trials (TR1, TR2, and TR3). In each trial, experiments were replicated three times (G1–G3). In each group (G1, G2 and G3), six different concentrations (C1–C6) of SPIONs were mixed with cells and cultured in the incubator for 72 h. The initial cell concentration, which is 2.5 × 105 cell/mL the cell viability (V), was measured after 72 h. The microscopic images (M) and impedance measurements (I) were obtained in eight different times (T1–T8). All experiments were repeated without cells to control the results. The entire experiment was performed for six months.
Meanwhile, the number of experiments per chamber is T R · C C · T · C · G = 864 . The number of experiments using PC and PCB electrode can reach 1728. By knowing that the microscopic images of experiments related to PCB electrodes were performed on a Petri dish, the total number of the experiment should be added using approximately TR × G × C = 54 Petri dishes.

4.1. Biological Effects

This section demonstrates the effect of SPIONs on the viability of cells. Figure 5 shows the percentages of alive and dead cells in the presence of six different concentrations of SPIONs (0, 25, 50, 100, 200 and 300 µg/mL) in the cell culture.
Figure 5. Viability Results. The percentages of both viable and dead N2a cells in the three different (a) group 1, (b) group 2 and (c) group 3 were graphed concerning six different categories A–F. 0, 25, 50, 100, 200 and 300 µg/mL SPIONs concentrations in the first trial.
In each group, the mean value of the three replicates was calculated for both alive and dead cells. Consistent with the results shown above, an inverse relationship between the concentration of SPIONs and cell viability was found. As seen in Figure 5, for C ≥ 50 µg/mL, the cell viability is high and almost invariant. On the other hand, the cells exposed to C ≥ 300 µg/mL SPIONs show the highest percentages of cell mortality. The same trend is observed using the PC array device. Low cell viability with percentages of 59, 47, 40% in higher concentrations of SPIONs, 100 µg/mL, 200 µg/mL, 300 µg/mL respectively is observed in PCB array device. All three trials on PCB and PC had shown that by increasing the concentrations of SPIONs, the cell viability was decreased, which may be due to the increased toxicity effect of SPIONs on cells. These results are in agreement with the results observed by Naqvi et al. [,] toxicity is amplified by higher doses of NPs.
Also, from the 25000 initial cell concentration at T1, all N2a cells in control with no SPIONS (C1) and those that treated with different concentrations of SPIONs (C2–C6) manifested an increased cell concentration after 72 h (T8). However, C4, C5, C6 showed lower cell concentration growth compared to C1. Relative to C1, the percent differences of cultured cells in C4, C5, C6, were 59%, 44% and 53% respectively, while 24% and 16% difference was observed at C2 and C3, respectively. Higher concentrations of SPIONs showed higher differences relative to the control, as shown in reference [].
Although the viability test was mainly determined using the Trypan Blue Dye Exclusion (TBDE), the number of cells were also counted using a Scepter™ 2.0 Handheld Cell Counter (see []). Figure 6 shows the mean values of counted cells using the TBDE and Scepter counter. Additionally, this figure shows a higher number of cells measured by Scepter cell counter compared to the one obtained in TBDE. The difference might be due to the presence of SPIONs’ aggregates along with the cells being detected, considering that Figure 6 shows the concentration for the total event, not the gated concentrations. Moreover, the calculated percent coefficient of variation (% CV) of the cell concentration in all concentrations (C1–C6) using TBDE is 8.85, 6.05, 8.69, 4.75, 6.32, 10.80, respectively. Relative to TBDE, using the resceptre cell counter, the percentages of CV in C1–C6 are 40.48%, 27.13%, 20.04%, 30.65%, 40.38%, and 56.88%, respectively. Comparing % CV results obtained using two different techniques, TBDE results shows less variation and consequently high accuracy, relative to the resceptre cell counter’s results.
Figure 6. Comparison of TBDE and the cell counter. The trypan blue dye exclusion (I) showing a lower number of cells counted in all the concentrations of SPIONs (C1 = 0, C2 = 25 µg/mL, C3 = 50 µg/mL, C4 = 100 µg/mL, C5 = 200 µg/mL, C6 = 300 µg/mL) compared to the Scepter Handheld Cell counter (II).

4.2. Morphological Effects

In this section, the adhesion, confluence and morphological changes of cells are evaluated using microscopic images. A motion 2.0 camera captured the microscopic changes of cells cultured on transparent electrodes and Petri dishes at different times (T1–T8). The images were captured from the same location of electrodes or Petri dishes and the same magnification (20 × 10 = 200). Figure 7a–f shows the N2a cells treated with C1-C6 concentrations of SPIONs respectively at T1 while Figure 7g–l shows the same cells incubated with the same concentrations of SPIONs at T8. These microscopic images are used to observe the growth, proliferation, and formation of neurite extensions of the N2a in the presence of various concentrations of SPIONs. In general, based on the results shown in Figure 7, the growth and proliferation of N2a are faster in the absence of SPIONS. A similar observation was pointed out in the study presented by Eustaquio and Leary (2012), where proliferation and differentiation of cells are affected by their exposure to nanoparticles []. Similarly, the decreased proliferation, brought about by an increasing amount of SPIONs, was also observed in the study performed by Lindemann et al. []. Also, Chen et al. (1997) pointed out that modifying the environment of cells such as cell substrate including the medium may alter cell behavior and shape, which can lead to decreased adhesion and increased cell death [].
Figure 7. Photomicrographs of untreated and treated N2a cells at the initial time (T1) and after 72 h’ (T8) incubation. Images in a, b, c, d, e, and f were taken at T1 while g, h, i, j, k, l at T8. a, g = untreated N2a; b, h = treated with 25 µg/mL; c, i = 50 µg/mL; d, j = 100 µg/mL; e, k = 100 µg/mL; f, l = 100 µg/mL SPIONs concentrations. Scale bar 100 µm.
In this experiment, each Petri dish and PCB/PC culture array were seeded with the same concentration of cells. As shown in Figure 7a–f, the cells had a round shaped at T1. At T8, the cells were completely adhered, differentiated and somehow developed neurites as seen in Figure 7g–l. As manifested in Figure 7g–h, the surfaces of Petri dishes were completely covered with cells where the concentrations of SPIONS were C1 and C2, respectively. This shows the highest cell confluence in the Petri dishes. However, Figure 7j–l shows less cell confluence on the surfaces of Petri dishes. Thus, it seems that longer neurites were generated to connect the nearby cells.
Additionally, by increasing the SPIONs, the size of SPIONs clusters is also increased as seen in Figure 7j–l.
Similarly, Figure 8a–l shows the growth of N2a cells on the surface of the electrode at T1 and T8 in different concentrations of SPIONs. Figure 8g and h show 95 to 100% cell confluence after 72 h of cell culture in an incubator. It is noteworthy that the optically transparent electrode array or so-called PC electrode array allowed us to count the number of cells using an optical microscope and measure the electrical impedance. The morphological changes as a result of the interaction of N2a to the different of SPIONs from T1–T8 are shown in reference [].
Figure 8. Photomicrograph of N2a cells exposed to the different concentrations of SPIONs on the surface of a 250μm diameter electrode on a clear polycarbonate substrate. Images in a, b, c, d, e, and f were taken at T1 while g, h, i, j, k, l at T8. a, g = untreated N2a; b, h = treated with 25 µg/mL; c, i = 50 µg/mL; d, j = 100 µg/mL; e, k = 100 µg/mL; f, l = 100 µg/mL SPIONs concentrations. Scale bar 100 µm.

4.3. Impedance Effects

As previously mentioned, in this paper, 1728 experiments were performed using PC and PCB electrodes. In each experiment, eight impedance measurements were performed at T1 to T8. Therefore, the number of the recorded complex impedance ZR + jZI values in 60 different frequencies is about 103,680, where ZR, ZI are real and imaginary values of impedance in each frequency, as seen in Table 6. In this table, the magnitude of impedances ( Z R 2 + Z I 2 ) is shown at different times (T1–T8). In this section, the results are demonstrated and discussed in three different forms—impedance spectroscopy, time-averaged impedance spectroscopy, and integration methods, as described in Section 3.
Table 6. A sample of impedance measurement in 8 different times, in the range of 0.1–100 KHz, when the concentration of SPIONs is C1.

4.3.1. Impedance Spectroscopy

This subsection includes the direct measurement of impedance spectroscopy at different times and different concentrations of SPIONs. Table 6 partially shows the magnitude of impedances at T1–T8 in various frequencies ranging from 0.1 Hz to 100,000 Hz.
Figure 9a shows the impedance spectroscopy results at different times (T1–T8) using the same concentration of SPIONs (C1). Similarly, Figure 9b–f shows the impedance spectroscopy results at C2–C6, respectively.
Figure 9. Impedance spectroscopy at different times T1 = A, T2 = B, T3 = C, T4 = D, T5 = E, T6 = F, T7 = G and T8 = H at different SPIONS concentrations: (a) C1, (b)C2, (c) C3, (d) C4, (e) C5 and (f) C6.

4.3.2. Time-Averaged Impedance Spectroscopy

Figure 10 shows the time-average of impedance spectroscopy in each frequency where A = N2a (control, C1), B = C2 with cells, C = C3 with cells, D = C4 with cells, E = C5 with cells, F = C6 with cells, G = CCM (Control, C1, without cell), and H = C2 without cells, I = C3 without cells, J = C4 without cells, K = C5 without cells and L = C6 without cells. Each curve in the groups 1, 2 or 3 (e.g., orange color, B) display the mean value of 8 impedance curves related to the same samples, in 8 different times. Also, Figure 10 shows the time-average effect of various samples on the impedance. The measurements were categorized into three different groups 1–3 (from the beginning to seventy-two hours of incubation). The highest impedance was manifested by the positive control group (N2a, with cells) while the lowest impedance value was observed from the negative control group (CCM, without cells). Based on the results shown in all groups in Figure 10, the presence of cells with or without SPIONs increase the impedance. This might be due to adhesion between the cell and electrodes. In the other hand, the lower the SPIONs concentration, the lower the impedance is expected to be in the sensing electrodes without the cells. This might be because the lower the SPIONs concentration becomes, the lower dielectric property can be expected to be. Another interesting outcome in the curves shown in Figure 10a is that the maximum impedance change is about 0.48–0.75 MΩ for SPIONs with concentrations ranging from 0 to 300 µg/mL. Therefore, the resolution of this measurement is about a 0.9 kΩ impedance change due to a 1 µg/mL SPIONs change. Based on the results shown in Figure 10b,c, the resolutions can be calculated similarly. The mean value of resolutions calculated in all three groups is about 520 Ω mL/µg. The highest impedance is clearly manifested among the lowest concentrations of SPIONs, C B and A mixed and cultured with cells. Meanwhile, the lowest impedance values were observed in the negative control, CCM (G) and CCM-SPIONs mixtures without cells (H-L).
Figure 10. Impedance Spectroscopy Readings of the control and different concentrations of N2a-SPIONs using a range of frequency from the log −1 to 5 (0.1 to 100000Hz). A 2.5 × 105 cells/mL concentration was used for the three groups((a) group 1, (b) group 2 and (c) group 3). Legend shows the different concentrations of SPIONs and the control groups where A = N2a (control), B = 25 µg/mL with cells, C = 50 µg/mL with cells, D = 100 µg/mL with cells, E = 200 µg/mL cells, F = 300 µg/mL with cells, G = CCM (Control), and H = 25 µg/mL without cells, I = 50 µg/mL without cells, J = 100 µg/mL without cells, K = 200 µg/mL without cells and L = 300 µg/mL without cells.

4.3.3. Integration Methods

As described in Section 3, the variation of surface area (∆S) under the impedance spectroscopy curves can be used as a measure to study the effect of cultured cells in the presence and absence of SPIONs. Figure 11a shows the calculated ∆S from the impedance spectroscopy results at six different SPIONs concentrations (C1–C6) at three different repeats (G1–G3), where the equation ZMAX−ZMIN was used. Similarly, Figure 11b,c show the calculated ∆S using the equations ZMAX−ZMIN(f) of TR1, TR2, TR3 and STD (Z0(f1) … Z72(fN), respectively.
Figure 11. Integrated Impedance Spectroscopy results using equations: (a), (b) and (c) at different concentration of SPIONs (C1–C6) and three different groups (G1–G3).
Based on the results shown in Figure 11, the higher the concentration, the lower ∆S is observed where the concentrations of SPIONs are C1, C2 or C3. Figure 11a–c shows a significant increase of ∆S at C4. Also, by increasing the SPIONs concentration (C5, C6), ∆S is decreased. Interestingly the same spike at C4 is observed in Trials 2 and 3. It is noteworthy, even though three different equations are used in Figure 11a–c, that the spike at C4 can be observed. One may argue that the shape and dimensions of electrodes, the material, size and concentration of nanoparticles can be considered as the main factors in the electrical models that have resulted in the creation of a spike at C4. Indeed, there are many other factors, such as the culture medium and even the alive cells that can affect the results shown in Figure 11a–c. A general justification can be provided using Figure 7j–l. As seen in Figure 7j, the presence of SPIONs with a high concentration (C4) has significantly resulted in decreasing the cell confluence. Instead of cells, the surface of the electrodes was coated with SPIONs. Therefore, it is expected that the charged SPIONs bond with the surface of electrodes and significantly increase the double layer capacitance and consequently increase the impedance in low frequencies. This change of impedance can justify the spike at C4. In the other hand, assuming that the SPIONs fully cover the surface of electrodes at C4, the increase of SPIONs concentration may result in creating larger aggregates and in affecting the cell attachment or cell growth as seen in Figure 7k,l.

4.3.4. Equivalent Electrical Circuit’s Method

Figure 12 shows the variation of capacitance, the series, and parallel resistances as a function of SPIONs concentration at T1, T2, T3, T4, T5, T6, T7, and T8. As seen in these Figures, the capacitance (C), series resistance (R1), and parallel resistance (R2) are in the range of 0.5–2.5 µF, 65–110 Ω, and 25–225 KΩ, respectively. Based on these results, the variation of SPIONs concentration or time do not significantly affect R1 and C. This is because R1 is proportional to the resistance of bulky medium that is highly conductive and the variation of SPIONs concentrations does not significantly change this conductivity. In the other hand, C is proportional to the double layer capacitance (DLC). DLC is affected by the attachment of cells or the distribution of SPIONs on the surface of electrodes. DLC is almost constant because of the higher attachment of cells, the lower surface area coated by SPIONs and vice versa. R2 in parallel with C changes over the times T1–T8. Similarly, R2 changes over the concentration of SPIONs (C1–C6). This might be due to the attachment or the deposit of molecules in the culture medium above the electrodes.
Figure 12. Equivalent electrical circuit including: (a) capacitance, (b) series resistance and (c) parallel resistance/impedance.

5. Future Discussion

Validating toxicity results depends on the sample size and replications. However, generating data with a large number of replicates is one of the challenges that any researcher needs to address. This section reveals the difficulty in obtaining a high volume of data in terms of economical and time elements involved in the study. This section also provides a glimpse of the ideal characteristics of the high throughput device for the future.

5.1. Economical Assessment

This subsection provides an estimated cost of the materials and chemicals used in the study and any high throughput toxicity assay. The estimated cost for performing 1728 experiments is about $2300. In a clinically relevant cytotoxicity study, by assuming C = 24 different concentrations of SPIONs with more than G = 12 times replicates and CC = 5 different cell concentrations, the number of experiments will approximately be equal to $184,000. The figures would prove a financial challenge in performing a number of experiments that obtain sufficient data to validate results and conclusions about toxicity studies. The high throughput platform containing a large number of micro-scale chambers enables parallel analysis that significantly decreases cost and the required time, as described in the next subsection.

5.2. Time Assessment

The experimental portion of this study involves different trials and replications that are time-consuming.
In this paper, in addition to biological and microscopic methods, a label-free impedance spectroscopy method was used as s new alternative technique for cellular analysis. The impedance readouts were recorded from eight different times (T1–T8) for each one six different (C1–C6) SPIONs concentrations with and without cells. As previously mentioned in chapter 3, this generates 1728 curves in almost 60 frequencies. In other words, this approximately counts up 100,000 impedance magnitude numbers. By assuming each number takes 5 s, the experiments can be completed after 6-days of continuous work. The required time for a clinically relevant cytotoxicity study is 80 × 6 = 480 days. In other words, it takes more than 16 months to complete the experiments. A high throughput platform containing at least 100 chambers in parallel for cell culture and impedance analysis can decrease the required time to less than 480/100 ~ 5 days.

5.3. High Throughput Analysis Device for the Future

Based on a large number of data generated to establish the interaction of SPIONs to the N2a cells, we anticipate that an automated high throughput screening system will be developed with highly sensitive electrodes to capture more complex activities of the cells. The high throughput analysis device can generate data faster. Since this study focused on the effect of SPIONs for a single type and concentration of cell, this can be further repeated using other types and concentrations of cells. Images depicting the morphology of the cells should be further examined to see potential pathologically significant results.

6. Conclusions

In this section, we demonstrated and discussed the viability test results using TBDE and Scepter cell counter. Based on the viability test results, there are higher chances for the N2a cells to be susceptible to higher concentrations of SPIONs, and consequently, this results in less viability at C4, C5, and C6. Also, the concentration of SPIONs is a critical factor for cell viability with increasing concentration correlated with increased toxicity. Based on our TBDE results, the viability is reduced to 47% and 40% in 200 and 300 µg/mL SPION concentrations, respectively.
Moreover, this investigation reports the effect of SPIONs on the cell viability of N2a cells using impedance spectroscopy, microscopy, and viability test assay. These methods were performed in part in multi-well settings, providing proof of principle that this approach is scalable, with potential for high throughput and high content analysis.
Also, microscopy and impedance spectroscopy methods were used to study the toxicity of SPIONs. The microscopic imaging technology used revealed that at a higher SPION concentration, cell density was compromised. Also, microscopic images showed that attachment and confluence of cells were significantly affected by the presence of SPIONs in the mixture. As per the results shown in this section, the exposure of cells to different concentrations of SPIONs affects the proliferation of cells, so that the maximum proliferation is observed when the concentration of SPIONs is at its minimum (C1). The number of N2A cells normally increases over time; however, the presence of SPIONs around the cells appears to restrict the ability of the cells to multiply.
Based on the results, a correlation between the impedance of sensing electrodes exposed to the cells treated with different SPIONs was demonstrated. Arguably, high-precision toxicity tests require a collection of large numbers of data points from multiple experiments. A high throughput impedance-based cell monitoring platform as reported in this study can be an efficient alternative to more traditional approaches, allowing us to perform a large number of experiments simultaneously with lower sample consumption and in a time effective manner. It was also shown that the variation of impedance is influenced by the concentration of both cells and SPIONs. However, the relationship between the changes of impedance or the related electrical components such as R1, R2, and C depends on various parameters such as the specification of electrodes in addition to other biological factors. The impedance spectroscopy offers great advantages of the label-free and low-cost method for assessment of the effectiveness of SPIONs on cells.
We had demonstrated that high throughput impedance-based label-free platform offers great advantages for studying SPIONs in a cell-based context, opening a window of opportunity to design and test the next generation SPIONs with reduced toxicity for biomedical or medical applications.

Author Contributions

S.A.T. performed all experiments and achieved results as part of her M.S.c. project under supervision of Professor E.G.-Z. and advisory of G.Z. E.G.-Z and G.Z. of this project were provided their comments in developing the concepts, performing the experiments, discussing the results and writing the paper.

Funding

This work was supported by NSERC Canada under grant number DG 504129. This paper is an invited paper and APC was waved.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Weinstein, J.S.; Varallyay, C.G.; Dosa, E.; Gahramanov, S.; Hamilton, B.; Rooney, W.D.; Muldoon, L.L.; Neuwelt, E.A. Superparamagnetic iron oxide nanoparticles: Diagnostic magnetic resonance imaging and potential therapeutic applications in neurooncology and central nervous system inflammatory pathologies, a review. J. Cereb. Blood Flow Metab. 2010, 30, 15–35. [Google Scholar] [CrossRef] [PubMed]
  2. Poller, J.M.; Zaloga, J.; Schreiber, E.; Unterweger, H.; Janko, C.; Radon, P.; Eberbeck, D.; Trahms, L.; Alexiou, C.; Friedrich, R.P. Selection of potential iron oxide nanoparticles for breast cancer treatment based on in vitro cytotoxicity and cellular uptake. Int. J. Nanomed. 2017, 12, 3207–3220. [Google Scholar] [CrossRef]
  3. Kang, Y.S.; Risbud, S.; Rabolt, J.F.; Stroeve, P. Synthesis and Characterization of Nanometer-Size Fe3O4 and γ-Fe2O3 Particles. Chem. Mater. 1996, 8, 2209–2211. [Google Scholar] [CrossRef]
  4. Oude Engberink, R.D.; van der Pol, S.M.A.; Blezer, E.L.A.; Döpp, E.A.; de Vries, H.E. Comparison of SPIO and USPIO for in Vitro Labeling of Human Monocytes: MR Detection and Cell Function. Radiology 2007, 243, 467–474. [Google Scholar] [CrossRef] [PubMed]
  5. Zlokovic, B.V. The Blood-Brain Barrier in Health and Chronic Neurodegenerative Disorders. Neuron 2008, 57, 178–201. [Google Scholar] [CrossRef] [PubMed]
  6. Re, F.; Gregori, M.; Masserini, M. Nanotechnology for neurodegenerative disorders. Maturitas 2012, 8, S51–S58. [Google Scholar]
  7. Masserini, M. Nanoparticles for Brain Drug Delivery. ISRN Biochem. 2013, 2013, 1–18. [Google Scholar] [CrossRef]
  8. Thomsen, L.B.; Linemann, T.; Pondman, K.M.; Lichota, J.; Kim, K.S.; Pieters, R.J.; Visser, G.M.; Moos, T. Uptake and transport of superparamagnetic iron oxide nanoparticles through human brain capillary endothelial cells. ACS Chem. Neurosci. 2013, 4, 1352–1360. [Google Scholar] [CrossRef]
  9. Mahmoudi, M.; Sant, S.; Wang, B.; Laurent, S.; Sen, T. Superparamagnetic iron oxide nanoparticles (SPIONs): Development, surface modification and applications in chemotherapy. Adv. Drug Deliv. Rev. 2011, 63, 24–46. [Google Scholar] [CrossRef]
  10. Singh, N.; Jenkins, G.J.; Asadi, R.; Doak, S.H. Potential toxicity of superparamagnetic iron oxide nanoparticles (SPION). Nano Rev. 2010, 1, 5358. [Google Scholar] [CrossRef]
  11. Eustaquio, T.; Leary, J.F. Single-cell nanotoxicity assays of superparamagnetic iron oxide nanoparticles. Methods Mol. Biol. 2012, 926, 69–85. [Google Scholar] [PubMed]
  12. Bashir, M.R.; Bhatti, L.; Marin, D.; Nelson, R.C. Emerging applications for ferumoxytol as a contrast agent in MRI. J. Magn. Reson. Imaging 2015, 41, 884–898. [Google Scholar] [CrossRef] [PubMed]
  13. Wang, C.; Ravi, S.; Martinez, G.V.; Chinnasamy, V.; Raulji, P.; Howell, M.; Davis, Y.; Mallela, J.; Seehra, M.S.; Mohapatra, S. Dual-purpose magnetic micelles for MRI and gene delivery. J. Control. Release 2012, 163, 82–92. [Google Scholar] [CrossRef] [PubMed]
  14. Varallyay, P.; Nesbit, G.; Muldoon, L.L.; Nixon, R.R.; Delashaw, J.; Cohen, J.I.; Petrillo, A.; Rink, D.; Neuwelt, E.A. Comparison of two superparamagnetic viral-sized iron oxide particles ferumoxides and ferumoxtran-10 with a gadolinium chelate in imaging intracranial tumors. Am. J. Neuroradiol. 2002, 23, 510–519. [Google Scholar] [PubMed]
  15. Rausch, M.; Sauter, A.; Frohlich, J.; Neubacher, U.; Radu, E.W.; Rudin, M. Dynamic patterns of USPIO enhancement can be observed in macrophages after ischemic brain damage. Magn. Reson. Med. 2001, 46, 1018–1022. [Google Scholar] [CrossRef] [PubMed]
  16. Yang, L.; Cao, Z.; Sajja, H.K.; Mao, H.; Wang, L.; Geng, H.; Xu, H.; Jiang, T.; Wood, W.C.; Nie, S.; et al. Development of receptor targeted magnetic iron oxide nanoparticles for efficient drug delivery and tumor imaging. J. Biomed. Nanotechnol. 2008, 4, 439–449. [Google Scholar] [CrossRef]
  17. Yang, H.H.; Zhang, S.Q.; Chen, X.L.; Zhuang, Z.X.; Xu, J.G.; Wang, X.R. Magnetite-Containing Spherical Silica Nanoparticles for Biocatalysis and Bioseparations. Anal. Chem. 2004, 76, 1316–1321. [Google Scholar] [CrossRef]
  18. Steitz, B.; Hofmann, H.; Kamau, S.W.; Hassa, P.O.; Hottiger, M.O.; von Rechenberg, B.; Hofmann-Amtenbrink, M.; Petri-Fink, A. Characterization of PEI-coated superparamagnetic iron oxide nanoparticles for transfection: Size distribution, colloidal properties and DNA interaction. J. Magn. Magn. Mater. 2007, 311, 300–305. [Google Scholar] [CrossRef]
  19. Estelrich, J.; Escribano, E.; Queralt, J.; Busquets, M.A. Iron oxide nanoparticles for magnetically-guided and magnetically-responsive drug delivery. Int. J. Mol. Sci. 2015, 16, 8070–8101. [Google Scholar] [CrossRef]
  20. Cheong, S.J.; Lee, C.M.; Kim, S.L.; Jeong, H.J.; Kim, E.M.; Park, E.H.; Kim, D.W.; Lim, S.T.; Sohn, M.H. Superparamagnetic iron oxide nanoparticles-loaded chitosan-linoleic acid nanoparticles as an effective hepatocyte-targeted gene delivery system. Int. J. Pharm. 2009, 372, 169–176. [Google Scholar] [CrossRef]
  21. Pöttler, M.; Fliedner, A.; Schreiber, E.; Janko, C.; Friedrich, R.P.; Bohr, C.; Döllinger, M.; Alexiou, C.; Dürr, S. Impact of Superparamagnetic Iron Oxide Nanoparticles on Vocal Fold Fibroblasts: Cell Behavior and Cellular Iron Kinetics. Nanoscale Res. Lett. 2017, 12, 284. [Google Scholar] [CrossRef] [PubMed][Green Version]
  22. Hong, H.; Yang, Y.; Zhang, Y.; Cai, W. Non-Invasive Cell Tracking in Cancer and Cancer Therapy. Curr. Top. Med. Chem. 2010, 10, 1237–1248. [Google Scholar] [CrossRef] [PubMed]
  23. De Leõn-Rodríguez, L.M.; Martins, A.F.; Pinho, M.C.; Rofsky, N.M.; Sherry, A.D. Basic MR relaxation mechanisms and contrast agent design. J. Magn. Reson. Imaging 2015, 42, 545–565. [Google Scholar] [CrossRef] [PubMed]
  24. Kirsch, J.K. Basic principles of magnetic resonance contrast agents. Top. Magn. Reson. Imaging 1991, 3, 1–18. [Google Scholar] [CrossRef] [PubMed]
  25. Yin, X.; Russek, S.E.; Zabow, G.; Sun, F.; Mohapatra, J.; Keenan, K.E.; Boss, M.A.; Zeng, H.; Liu, J.P.; Viert, A.; et al. Large T1contrast enhancement using superparamagnetic nanoparticles in ultra-low field MRI. Sci. Rep. 2018, 8, 11863. [Google Scholar] [CrossRef] [PubMed]
  26. Mendonca Dias, M.H.; Lauterbur, P.C. Ferromagnetic particles as contrast agents for magnetic resonance imaging of liver and spleen. Magn. Reson. Med. 1986, 3, 328–330. [Google Scholar] [CrossRef] [PubMed]
  27. Gupta, A.K.; Gupta, M. Cytotoxicity suppression and cellular uptake enhancement of surface modified magnetic nanoparticles. Biomaterials 2005, 26, 1565–1573. [Google Scholar] [CrossRef]
  28. Petri-Fink, A.; Chastellain, M.; Juillerat-Jeanneret, L.; Ferrari, A.; Hofmann, H. Development of functionalized superparamagnetic iron oxide nanoparticles for interaction with human cancer cells. Biomaterials 2005, 26, 2685–2694. [Google Scholar] [CrossRef]
  29. Fu, T.; Kong, Q.; Sheng, H.; Gao, L. Value of Functionalized Superparamagnetic Iron Oxide Nanoparticles in the Diagnosis and Treatment of Acute Temporal Lobe Epilepsy on MRI. Neural Plast. 2016, 2016, 1–12. [Google Scholar] [CrossRef]
  30. Wang, Y.; Wang, Y.; Sun, R.; Wu, X.; Chu, X.; Zhou, S.; Hu, X.; Gao, L.; Kong, Q. The treatment value of IL-1β monoclonal antibody under the targeting location of alpha-methyl-l-tryptophan and superparamagnetic iron oxide nanoparticles in an acute temporal lobe epilepsy model 11 Medical and Health Sciences 1109 Neurosciences. J. Transl. Med. 2018, 16, 337. [Google Scholar] [CrossRef]
  31. Corchero, J.L.; Villaverde, A. Biomedical applications of distally controlled magnetic nanoparticles. Trends Biotechnol. 2009, 27, 468–476. [Google Scholar] [CrossRef]
  32. Phukan, G.; Shin, T.H.; Shim, J.S.; Paik, M.J.; Lee, J.K.; Choi, S.; Kim, Y.M.; Kang, S.H.; Kim, H.S.; Kang, Y.; et al. Silica-coated magnetic nanoparticles impair proteasome activity and increase the formation of cytoplasmic inclusion bodies in vitro. Sci. Rep. 2016, 6, 29095. [Google Scholar] [CrossRef] [PubMed]
  33. Wuest, D.M.; Lee, K.H. Optimization of endothelial cell growth in a murine in vitro blood-brain barrier model. Biotechnol. J. 2012, 7, 409–417. [Google Scholar] [CrossRef]
  34. Helms, H.C.; Abbott, N.J.; Burek, M.; Cecchelli, R.; Couraud, P.O.; Deli, M.A.; Förster, C.; Galla, H.J.; Romero, I.A.; Shusta, E.V.; et al. In vitro models of the blood-brain barrier: An overview of commonly used brain endothelial cell culture models and guidelines for their use. J. Cereb. Blood Flow Metab. 2016, 36, 862–890. [Google Scholar] [CrossRef] [PubMed]
  35. Shi, D.; Mi, G.J.; Bhattacharya, S.; Nayar, S.; Webster, T.J. Optimizing superparamagnetic iron oxide nanoparticles as drug carriers using an in vitro blood-brain barrier model. Int. J. Nanomed. 2016, 11, 5371–5379. [Google Scholar] [CrossRef] [PubMed]
  36. Jiang, C.; Yang, S.; Gan, N.; Pan, H.; Liu, H. A method for determination of [Fe3+]/[Fe2+] ratio in superparamagnetic iron oxide. J. Magn. Magn. Mater. 2017, 439, 126–134. [Google Scholar] [CrossRef]
  37. Huber, D.L. Synthesis, properties, and applications of iron nanoparticles. Small 2005, 1, 482–501. [Google Scholar] [CrossRef] [PubMed]
  38. Li, L.H.; Xiao, J.; Liu, P.; Yang, G.W. Super adsorption capability from amorphousization of metal oxide nanoparticles for dye removal. Sci. Rep. 2015, 5, 9028. [Google Scholar] [CrossRef]
  39. Maurizi, L.; Claveau, A.; Hofmann, H. Polymer adsorption on iron oxide nanoparticles for one-step amino-functionalized silica encapsulation. J. Nanomater. 2015, 16, 239. [Google Scholar] [CrossRef]
  40. Vermeij, E.A.; Koenders, M.I.; Bennink, M.B.; Crowe, L.A.; Maurizi, L.; Vallée, J.P.; Hofmann, H.; Van Den Berg, W.B.; Van Lent, P.L.E.M.; Van De Loo, F.A.J. The in-vivo use of superparamagnetic iron oxide nanoparticles to detect inflammation elicits a cytokine response but does not aggravate experimental arthritis. PLoS ONE 2015, 10, e0126687. [Google Scholar] [CrossRef]
  41. Galuppo, L.D.; Kamau, S.W.; Steitz, B.; Hassa, P.O.; Hilbe, M.; Vaughan, L.; Koch, S.; Fink-Petri, A.; Hofman, M.; Hofman, H.; et al. Gene expression in synovial membrane cells after intraarticular delivery of plasmid-linked superparamagnetic iron oxide particles—A preliminary study in sheep. J. Nanosci. Nanotechnol. 2006, 6, 2841–2852. [Google Scholar] [CrossRef] [PubMed]
  42. Polikov, V.; Block, M.; Zhang, C.; Reichert, W.M.; Hong, J.S. In Vitro Models for Neuroelectrodes: A Paradigm for Studying Tissue–Materials Interactions in the Brain. In Indwelling Neural Implants: Strategies for Contending with the In Vivo Environment; CRC Press/Taylor & Francis: Boca Raton, FL, USA, 2008. [Google Scholar]
  43. Påhlman, S.; Mamaeva, S.; Meyerson, G.; Mattsson, M.E.; Bjelfman, C.; Ortoft, E.; Hammerling, U. Human neuroblastoma cells in culture: A model for neuronal cell differentiation and function. Acta Physiol. Scand. Suppl. 1990, 592, 25–37. [Google Scholar] [PubMed]
  44. Rall, W. Electrophysiology of a Dendritic Neuron Model. Biophys. J. 1962, 2, 145–167. [Google Scholar] [CrossRef]
  45. Petri-Fink, A.; Steitz, B.; Finka, A.; Salaklang, J.; Hofmann, H. Effect of cell media on polymer coated superparamagnetic iron oxide nanoparticles (SPIONs): Colloidal stability, cytotoxicity, and cellular uptake studies. Eur. J. Pharm. Biopharm. 2008, 68, 129–137. [Google Scholar] [CrossRef] [PubMed]
  46. Safi, M.; Courtois, J.; Seigneuret, M.; Conjeaud, H.; Berret, J.F. The effects of aggregation and protein corona on the cellular internalization of iron oxide nanoparticles. Biomaterials 2011, 32, 9353–9363. [Google Scholar] [CrossRef]
  47. Hauser, A.K.; Mitov, M.I.; Daley, E.F.; McGarry, R.C.; Anderson, K.W.; Hilt, J.Z. Targeted iron oxide nanoparticles for the enhancement of radiation therapy. Biomaterials 2016, 105, 127–135. [Google Scholar] [CrossRef] [PubMed]
  48. Wiogo, H.T.R.; Lim, M.; Bulmus, V.; Yun, J.; Amal, R. Stabilization of magnetic iron oxide nanoparticles in biological media by fetal bovine serum (FBS). Langmuir 2011, 27, 843–850. [Google Scholar] [CrossRef]
  49. Singh, S.; Kumar, S.; Yata, V.K. Health Benefits and Potential Risks of Nanostructured Materials. In Environmental Chemistry for a Sustainable World; Dasgupta, N., Ranjan, S., Lichtfouse, E., Eds.; Springer: Cham, Germany, 2019; Volume 21, pp. 109–142. [Google Scholar]
  50. Lesniak, A.; Salvati, A.; Santos-Martinez, M.J.; Radomski, M.W.; Dawson, K.A.; Åberg, C. Nanoparticle adhesion to the cell membrane and its effect on nanoparticle uptake efficiency. J. Am. Chem. Soc. 2013, 135, 1438–1444. [Google Scholar] [CrossRef]
  51. Aggarwal, P.; Hall, J.B.; McLeland, C.B.; Dobrovolskaia, M.A.; McNeil, S.E. Nanoparticle interaction with plasma proteins as it relates to particle biodistribution, biocompatibility and therapeutic efficacy. Adv. Drug Deliv. Rev. 2009, 61, 428–437. [Google Scholar] [CrossRef]
  52. Verma, A.; Stellacci, F. Effect of surface properties on nanoparticle-cell interactions. Small 2010, 6, 12–21. [Google Scholar] [CrossRef]
  53. Schütz, I.; Lopez-Hernandez, T.; Gao, Q.; Puchkov, D.; JaBerlinbs, S.; Nordmeyer, D.; Schmudde, M.; Rühl, E.; Graf, C.M.; Haucke, V. Lysosomal dysfunction caused by cellular accumulation of silica nanoparticles. J. Biol. Chem. 2016, 291, 14170–14184. [Google Scholar] [CrossRef] [PubMed]
  54. Karataş, Ö.F.; Sezgin, E.; Aydin, Ö.; Çulha, M. Interaction of gold nanoparticles with mitochondria. Colloids Surf. B Biointerfaces 2009, 71, 315–318. [Google Scholar] [CrossRef] [PubMed]
  55. Xu, C.; Xie, J.; Kohler, N.; Walsh, E.G.; Chin, Y.E.; Sun, S. Monodisperse magnetite nanoparticles coupled with nuclear localization signal peptide for cell-nucleus targeting. Chem. Asian J. 2008, 3, 548–552. [Google Scholar] [CrossRef] [PubMed]
  56. McNamara, A.L.; Kam, W.W.Y.; Scales, N.; McMahon, S.J.; Bennett, J.W.; Byrne, H.L.; Schuemann, J.; Paganetti, H.; Banati, R.; Kuncic, Z. Dose enhancement effects to the nucleus and mitochondria from gold nanoparticles in the cytosol. Phys. Med. Biol. 2016, 61, 5993–6010. [Google Scholar] [CrossRef] [PubMed]
  57. Baranes, K.; Shevach, M.; Shefi, O.; Dvir, T. Gold Nanoparticle-Decorated Scaffolds Promote Neuronal Differentiation and Maturation. Nano Lett. 2016, 16, 2916–2920. [Google Scholar] [CrossRef] [PubMed]
  58. Chen, H.; Sun, J.; Wang, Z.; Zhou, Y.; Lou, Z.; Chen, B.; Wang, P.; Guo, Z.; Tang, H.; Ma, J.; et al. Magnetic Cell-Scaffold Interface Constructed by Superparamagnetic IONP Enhanced Osteogenesis of Adipose-Derived Stem Cells. ACS Appl. Mater. Interfaces 2018, 10, 44279–44289. [Google Scholar] [CrossRef] [PubMed]
  59. Poot, M.; Rosato, M.; Rabinovitch, P.S. Analysis of Cell Proliferation and Cell Survival by Continuous BrdU Labeling and Multivariate Flow Cytometry. Curr. Protoc. Cytom. 2001, 15, 7–14. [Google Scholar]
  60. Rothaeusler, K.; Baumgarth, N. Assessment of cell proliferation by 5-bromodeoxyuridine (BrdU) labeling for multicolor flow cytometry. Curr. Protoc. Cytom. 2007, 40, 7–31. [Google Scholar]
  61. Strober, W. Trypan blue exclusion test of cell viability. Curr. Protoc. Immunol. 2001, 21, A.3B.1–A.3B.2. [Google Scholar]
  62. Fritzsche, M.; Fredriksson, J.M.; Carlsson, M.; Mandenius, C.F. A cell-based sensor system for toxicity testing using multiwavelength fluorescence spectroscopy. Anal. Biochem. 2009, 387, 271–275. [Google Scholar] [CrossRef]
  63. Moczko, E.; Mirkes, E.M.; Cáceres, C.; Gorban, A.N.; Piletsky, S. Fluorescence-based assay as a new screening tool for toxic chemicals. Sci. Rep. 2016, 6, 33922. [Google Scholar] [CrossRef] [PubMed]
  64. Ceriotti, L.; Ponti, J.; Colpo, P.; Sabbioni, E.; Rossi, F. Assessment of cytotoxicity by impedance spectroscopy. Biosens. Bioelectron. 2007, 22, 3057–3063. [Google Scholar] [CrossRef] [PubMed]
  65. Ceriotti, L.; Ponti, J.; Broggi, F.; Kob, A.; Drechsler, S.; Thedinga, E.; Colpo, P.; Sabbioni, E.; Ehret, R.; Rossi, F. Real-time assessment of cytotoxicity by impedance measurement on a 96-well plate. Sens. Actuators B Chem. 2007, 123, 769–778. [Google Scholar] [CrossRef]
  66. Zhang, X.; Li, F.; Nordin, A.N.; Tarbell, J.; Voiculescu, I. Toxicity studies using mammalian cells and impedance spectroscopy method. Sens. Bio-Sens. Res. 2015, 3, 112–121. [Google Scholar] [CrossRef]
  67. Newbold, C.; Richardson, R.; Millard, R.; Huang, C.; Milojevic, D.; Shepherd, R.; Cowan, R. Changes in biphasic electrode impedance with protein adsorption and cell growth. J. Neural Eng. 2010, 7, 056011. [Google Scholar] [CrossRef] [PubMed]
  68. Zhu, X.; Hondroulis, E.; Liu, W.; Li, C.Z. Biosensing approaches for rapid genotoxicity and cytotoxicity assays upon nanomaterial exposure. Small 2013, 9, 1821–1830. [Google Scholar] [CrossRef] [PubMed]
  69. Sadik, O.A.; Zhou, A.L.; Kikandi, S.; Du, N.; Wang, Q.; Varner, K. Sensors as tools for quantitation, nanotoxicity and nanomonitoring assessment of engineered nanomaterials. J. Environ. Monit. 2009, 11, 1782. [Google Scholar] [CrossRef]
  70. Özel, R.E.; Liu, X.; Alkasir, R.S.J.; Andreescu, S. Electrochemical methods for nanotoxicity assessment. TrAC Trends Anal. Chem. 2014, 59, 112–120. [Google Scholar] [CrossRef]
  71. Marcus, M.; Karni, M.; Baranes, K.; Levy, I.; Alon, N.; Margel, S.; Shefi, O. Iron oxide nanoparticles for neuronal cell applications: Uptake study and magnetic manipulations. J. Nanobiotechnol. 2016, 14, 37. [Google Scholar] [CrossRef]
  72. Mahmoudi, M.; Simchi, A.; Imani, M.; Shokrgozar, M.A.; Milani, A.S.; Häfeli, U.O.; Stroeve, P. A new approach for the in vitro identification of the cytotoxicity of superparamagnetic iron oxide nanoparticles. Colloids Surf. B Biointerfaces 2010, 75, 300–309. [Google Scholar] [CrossRef]
  73. Jarockyte, G.; Daugelaite, E.; Stasys, M.; Statkute, U.; Poderys, V.; Tseng, T.C.; Hsu, S.H.; Karabanovas, V.; Rotomskis, R. Accumulation and toxicity of superparamagnetic iron oxide nanoparticles in cells and experimental animals. Int. J. Mol. Sci. 2016, 17, 1193. [Google Scholar] [CrossRef] [PubMed]
  74. Magdolenova, Z.; Drlickova, M.; Henjum, K.; Rundén-Pran, E.; Tulinska, J.; Bilanicova, D.; Pojana, G.; Kazimirova, A.; Barancokova, M.; Kuricova, M.; et al. Coating-dependent induction of cytotoxicity and genotoxicity of iron oxide nanoparticles. Nanotoxicology 2015, 9, 44–56. [Google Scholar] [CrossRef]
  75. Ying, E.; Hwang, H.M. In vitro evaluation of the cytotoxicity of iron oxide nanoparticles with different coatings and different sizes in A3 human T lymphocytes. Sci. Total Environ. 2010, 408, 4475–4481. [Google Scholar] [CrossRef]
  76. Sun, Z.; Yathindranath, V.; Worden, M.; Thliveris, J.A.; Chu, S.; Parkinson, F.E.; Hegmann, T.; Miller, D.W. Characterization of cellular uptake and toxicity of aminosilane-coated iron oxide nanoparticles with different charges in central nervous system-relevant cell culture models. Int. J. Nanomed. 2013, 8, 961–970. [Google Scholar] [CrossRef] [PubMed]
  77. Mbeh, D.A.; Mireles, L.K.; Stanicki, D.; Tabet, L.; Maghni, K.; Laurent, S.; Sacher, E.; Yahia, L. Human Alveolar Epithelial Cell Responses to Core-Shell Superparamagnetic Iron Oxide Nanoparticles (SPIONs). Langmuir 2015, 31, 3829–3839. [Google Scholar] [CrossRef]
  78. Invitrogen. PrestoBlue Cell Viability Reagent Documentation. A13261. 2010. Available online: http://tools.thermofisher.com/content/sfs/manuals/PrestoBlue_Reagent_PIS_15Oct10.pdf (accessed on 6 June 2019).
  79. Soenen, S.J.H.; Himmelreich, U.; Nuytten, N.; De Cuyper, M. Cytotoxic effects of iron oxide nanoparticles and implications for safety in cell labelling. Biomaterials 2011, 32, 195–205. [Google Scholar] [CrossRef] [PubMed]
  80. Petters, C.; Dringen, R. Accumulation of iron oxide nanoparticles by cultured primary neurons. Neurochem. Int. 2015, 81, 1–9. [Google Scholar] [CrossRef] [PubMed]
  81. Munnier, E.; Cohen-Jonathan, S.; Hervé, K.; Linassier, C.; Soucé, M.; Dubois, P.; Chourpa, I. Doxorubicin delivered to MCF-7 cancer cells by superparamagnetic iron oxide nanoparticles: Effects on subcellular distribution and cytotoxicity. J. Nanopart. Res. 2011, 13, 959–971. [Google Scholar] [CrossRef]
  82. Calero, M.; Chiappi, M.; Lazaro-Carrillo, A.; Rodríguez, M.J.; Chichón, F.J.; Crosbie-Staunton, K.; Prina-Mello, A.; Volkov, Y.; Villanueva, A.; Carrascosa, J.L. Characterization of interaction of magnetic nanoparticles with breast cancer cells. J. Nanobiotechnol. 2015, 13, 16. [Google Scholar] [CrossRef]
  83. K’Owino, I.O.; Sadik, O.A. Impedance spectroscopy: A powerful tool for rapid biomolecular screening and cell culture monitoring. Electroanalysis 2005, 17, 2101–2113. [Google Scholar] [CrossRef]
  84. Giaever, I.; Keese, C.R. Monitoring fibroblast behavior in tissue culture with an applied electric field. Proc. Natl. Acad. Sci. USA 1984, 81, 3761–3764. [Google Scholar] [CrossRef] [PubMed]
  85. Rahman, A.R.A.; Register, J.; Vuppala, G.; Bhansali, S. Cell culture monitoring by impedance mapping using a multielectrode scanning impedance spectroscopy system (CellMap). Physiol. Meas. 2008, 29, S227–S239. [Google Scholar] [CrossRef] [PubMed]
  86. Sarro, E.; Lecina, M.; Fontova, A.; Sola, C.; Godia, F.; Cairo, J.J.; Bragos, R. Electrical impedance spectroscopy measurements using a four-electrode configuration improve on-line monitoring of cell concentration in adherent animal cell cultures. Biosens. Bioelectron. 2012, 31, 257–263. [Google Scholar] [CrossRef]
  87. Valero, T.; Jacobs, T.; Moschopoulou, G.; Naumann, M.; Hauptmann, P.; Kintzios, S. Electrical impedance analysis of N2a neuroblastoma cells in gel matrices after ACh-receptor triggering with an impedimetric biosensor. Procedia Chem. 2009, 1, 734–737. [Google Scholar] [CrossRef]
  88. Seriburi, P.; McGuire, S.; Shastry, A.; Böhringer, K.F.; Meldrum, D.R. Measurement of the cell-substrate separation and the projected area of an individual adherent cell using electric cell-substrate impedance sensing. Anal. Chem. 2008, 80, 3677–3683. [Google Scholar] [CrossRef] [PubMed]
  89. Witzel, F.; Fritsche-Guenther, R.; Lehmann, N.; Sieber, A.; Blüthgen, N. Analysis of impedance-based cellular growth assays. Bioinformatics 2015, 31, 2705–2712. [Google Scholar] [CrossRef] [PubMed]
  90. Lo, C.M.; Keese, C.R.; Giaever, I. Impedance analysis of MDCK cells measured by electric cell-substrate impedance sensing. Biophys. J. 1995, 69, 2800–2807. [Google Scholar] [CrossRef]
  91. Wang, W.; Foley, K.; Shan, X.; Wang, S.; Eaton, S.; Nagaraj, V.J.; Wiktor, P.; Patel, U.; Tao, N. Single cells and intracellular processes studied by a plasmonic-based electrochemical impedance microscopy. Nat. Chem. 2011, 3, 249–255. [Google Scholar] [CrossRef]
  92. Collins, A.R.; Annangi, B.; Rubio, L.; Marcos, R.; Dorn, M.; Merker, C.; Estrela-Lopis, I.; Cimpan, M.R.; Ibrahim, M.; Cimpan, E.; et al. High throughput toxicity screening and intracellular detection of nanomaterials. Wiley Interdiscip. Rev. Nanomed. Nanobiotechnol. 2017, 9, e1413. [Google Scholar] [CrossRef]
  93. Moe, B.; Gabos, S.; Li, X.F. Real-time cell-microelectronic sensing of nanoparticle-induced cytotoxic effects. Anal. Chim. Acta 2013, 789, 83–90. [Google Scholar] [CrossRef]
  94. Ghafar-Zadeh, E.; Sawan, M.; Chodavarapu, V.P. Micro-Organism-on-Chip: Emerging direct-write CMOS-Based platform for biological applications. IEEE Trans. Biomed. Circuits Syst. 2009, 3, 212–219. [Google Scholar] [CrossRef] [PubMed]
  95. Williams, J.C.; Hippensteel, J.A.; Dilgen, J.; Shain, W.; Kipke, D.R. Complex impedance spectroscopy for monitoring tissue responses to inserted neural implants. J. Neural Eng. 2007, 4, 410–423. [Google Scholar] [CrossRef] [PubMed]
  96. Szulcek, R.; Bogaard, H.J.; van Nieuw Amerongen, G.P. Electric Cell-substrate Impedance Sensing for the Quantification of Endothelial Proliferation, Barrier Function, and Motility. J. Vis. Exp. 2014, 85, e51300. [Google Scholar] [CrossRef] [PubMed]
  97. Arias, L.R.; Perry, C.A.; Yang, L. Real-time electrical impedance detection of cellular activities of oral cancer cells. Biosens. Bioelectron. 2010, 25, 2225–2231. [Google Scholar] [CrossRef] [PubMed]
  98. Asphahani, F.; Wang, K.; Thein, M.; Veiseh, O.; Yung, S.; Xu, J.; Zhang, M. Single-cell bioelectrical impedance platform for monitoring cellular response to drug treatment. Phys. Biol. 2011, 8, 015006. [Google Scholar] [CrossRef] [PubMed]
  99. Peters, M.F.; Lamore, S.D.; Guo, L.; Scott, C.W.; Kolaja, K.L. Human Stem Cell-Derived Cardiomyocytes in Cellular Impedance Assays: Bringing Cardiotoxicity Screening to the Front Line. Cardiovasc. Toxicol. 2015, 15, 127–139. [Google Scholar] [CrossRef]
  100. Kuzmanov, I.; Herrmann, A.M.; Galla, H.-J.; Meuth, S.G.; Wiendl, H.; Klotz, L. An In Vitro Model of the Blood-brain Barrier Using Impedance Spectroscopy: A Focus on T Cell-endothelial Cell Interaction. J. Vis. Exp. 2016, 118, e54592. [Google Scholar] [CrossRef]
  101. Klebe, R.J. Klebe and Ruddle Neuroblastoma: Cell culture analysis of a differentiating stem cell system. J. Cell Biol. 1969, 43, 69A. [Google Scholar]
  102. SkySpring Nanomaterials Inc. Iron Oxide Nanoparticles/Nanopowder (Fe3O4, 10~15 nm, 98+%). 2016. Available online: https://ssnano.com/inc/sdetail/iron-oxide-nanoparticles---nanopowder---fe3o4--10-15nm--98---/123/8881 (accessed on 6 June 2019).
  103. Jiang, L.; Liu, J.; Shi, J.; Li, X.; Li, H.; Liu, J.; Ye, J.; Chen, Y. Impedance monitoring of cell adhesion and growth on mesoporous membrane. Microelectron. Eng. 2011, 88, 1722–1725. [Google Scholar] [CrossRef]
  104. Naqvi, S.; Samim, M.; Abdin, M.Z.; Ahmed, F.J.; Maitra, A.N.; Prashant, C.K.; Dinda, A.K. Concentration-dependent toxicity of iron oxide nanoparticles mediated by increased oxidative stress. Int. J. Nanomed. 2010, 5, 983–989. [Google Scholar] [CrossRef]
  105. Tan, S. Toward A High Throughput Label-Free Platform for Monitoring Interaction Between Cells and Superparamagnetic Iron Oxide Nanoparticles. In Proceedings of the 2018 IEEE Life Sciences Conference (LSC), Montreal, QC, Canada, 28–30 October 2018. [Google Scholar]
  106. Lindemann, A.; Lüdtke-Buzug, K.; Fräderich, B.M.; Gräfe, K.; Pries, R.; Wollenberg, B. Biological impact of superparamagnetic iron oxide nanoparticles for magnetic particle imaging of head and neck cancer cells. Int. J. Nanomed. 2014, 9, 5025–5040. [Google Scholar] [CrossRef] [PubMed]
  107. Chen, C.S.; Mrksich, M.; Huang, S.; Whitesides, G.M.; Ingber, D.E. Geometric control of cell life and death. Science 1997, 276, 1425–1428. [Google Scholar] [CrossRef] [PubMed]

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