Cell image database for citotoxicity test

Cell image database for citotoxicity test

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Is there any cell image database for citotoxicity tests? I know that there are several image databases available (like this, this and this one), but none of them have the images for citotoxicity tests.

Thanks in advance,


The cytotoxicity test is designed to evaluate the general toxicity of medical devices and materials. Testing involves extracting devices in a cell culture media and then exposing the extract fluid to mouse fibroblast cells (L929). The cells are allowed to grow in the extract fluid for a specified amount of time before the cells are evaluated using either qualitative or quantitative methods. The test is performed on all medical devices with patient contact, raw materials, and devices undergoing a cleaning validation or residual manufacturing.

Download the biocompatibility test matrix. [Based on ISO 10993-1:2010 (E) and FDA “Use of international standard ISO 10993-1”]

Applicable Standards

Testing Locations

Study Outline for Cytotoxicity/MEM/Agar Overlay

MEM Elution
Devices/materials are generally extracted in serum-supplemented mammalian cell culture media (MEM) 37 ± 1ºC. After extraction, the extracts are placed in contact with a monolayer of L-929 cells (mouse fibroblasts). The cells are then allowed to grow in the extraction fluid for a specified amount of time before the cells are evaluated using either qualitative or quantitative methods.


Qualitative evaluation involves observing the cells under a microscope and assigning a cytotoxic grade (0-4). The grade is based on an estimated percent lysis (death) and on the morphology (appearance) of the cells. Test materials pass the assay if the cytotoxic score is ≤ 2 (≤ 50% lysis).


Quantitative evaluation utilizes a tetrazolium dye which is used to assess the metabolic activity of cells. The results are reported as percent viability (% living cells). Test materials pass the assay if the percent viability if ≥ 70%. Multiple dilutions of the test article extract are generally included with each assay.

Agar Overlay
Materials are generally tested by surface area using at least 100 mm 2 of material per well. Weight may also be used for liquids, gels, or powders using at least 100 mg per well. The material is placed on a layer of agarose that is placed on top of a monolayer of L-929 cells and incubated for 24 – 26 hours at 37 ± 1ºC in 5 ± 1% CO2. After incubation, the zone of cell destruction is measured and scored based on a 0 – 4 scale listed in AAMI/ANSI/ISO 10993-5. The material meets ISO requirements if the cytotoxic response is not greater than grade 2 (mildly reactive). Although Agar Overlay has been historically an accepted test method it may not be appropriate when submitting to certain regulatory bodies.

Cytotoxicity Failures

Occasionally, a device or material will exhibit a level of cytotoxic reactivity that is higher than what is allowed by the ANSI/AAMI/ISO 10993-5 standard and will result in a failed test. Although your product may have failed a cytotoxicity test, it does not necessarily mean that your device or material is unsafe for clinical use. It simply means that you are obligated to identify the source of failure and assess any toxicological risks.

Our Experts Can Help

There are several possible causes for cytotoxicity failure, and Nelson Labs offers services to help you identify and assess the failure. From there, our experts can assess any potential toxicological risk to patient safety.

We evaluate the materials and processes associated with the device. Based on this information, our experts will often recommend targeted analytical chemistry to determine the cause of the failure. We can then work with clients to justify the failure through testing and assessment.

A discussion with our experts to identify the cause of cytotoxicity failure and develop an action plan often leads to manufacturers successfully submitting their device for regulatory approval without any further action.

If you have additional questions about Cytotoxicity, or would like to consult with the experts at Nelson Labs, just send us a request or call us at +1 (801) 290-7500.

Cell image database for citotoxicity test - Biology

Visual observation is a powerful approach for screening bioactive compounds that can facilitate the discovery of attractive druggable targets following their chemicobiological validation. So far, many high-content approaches, using sophisticated imaging technology and bioinformatics, have been developed. In our study, we aimed to develop a simpler method that focuses on intact cell images because we found that dynamic changes in morphology are informative, often reflecting the mechanism of action of a drug. Here, we constructed a chemical-genetic phenotype profiling system, based on the high-content cell morphology database Morphobase. This database compiles the phenotypes of cancer cell lines that are induced by hundreds of reference compounds, wherein those of well-characterized anticancer drugs are classified by mode of action. Furthermore, we demonstrate the applicability of this system in identifying NPD6689, NPD8617, and NPD8969 as tubulin inhibitors.

Graphical Abstract


► Development of an encyclopedia of cell morphology, Morphobase ► Small molecules classified by mode of action with Morphobase ► Morphobase system rapidly predicts molecular targets of compounds ► NPD6689 targets tubulin and is a lead for a class of antitubulin drugs

ATP assays

Most assays use a cell membrane permeabilization agent to release ATP light is produced using ATP-dependent luciferase. Other ATP assays use the ATP-dependent phosphorylation of glycerol (or other substrates).

Luminescence ATP assay ab113849: No-wash assay. Luminometric plate reader.

Luminescence ADP/ATP assay ab65313: No-wash assay. After ATP analysis, ADP is converted to ATP for detection. Luminometric plate reader.

​ ATP phosphorylation assay ab83355: No-wash assay used with cell lysates. Not as sensitive as luminescence assays. Fluorometric (Ex/Em 535/587 nm) is more sensitive than colorimetric. Plate reader.

Cell Systems Science Group

The Cell Systems Science Group conducts research in measurements and models that support the understanding of complex biological phenomena at the cellular and subcellular level. The group focuses on the cell as a system and tools that can make measurements and characterize the system properties.

The Cell Systems Science Group contributes to the new post-genomic era with research in measurements and models that support the understanding of complex biological phenomena at the cellular and subcellular levels. The group focuses on the cell as a system and tools that can make measurements and characterize the system properties. This is achieved through bioimaging and other cytometry techniques, measurements that assess protein and gene function within living cells, experimental design, and bioinformatics. We are focusing our efforts on measurements for assessing the process of creation, maintenance and differentiation of pluripotent stem cells in addition to cell lines and engineered cells to understand cellular dynamics. The group emphasizes new measurement tool development and protocols that ensure reliability and comparability of cell assay and imaging-based measurements and appropriate data analysis and data handling pipelines. These efforts assist basic biomedical research, biomanufacturing of regenerative medicine products, non-animal toxicology testing, drug development and testing, precision medicine, and other applications that depend on understanding and predicting complex cellular activities.


Hereditary sensory and autonomic neuropathy (HSAN) types IA and IC (A/C) are inherited diseases that mainly affect the sensory and autonomic functions of the peripheral nervous system. The clinical hallmark of the diseases is loss of pain and temperature sensations in the distal extremities. In some cases, it is accompanied by hypohidrosis (diminished sweating) (Auer-Grumbach, 2008). In general, the diseases have a late onset varying between the second and the fifth decade of life (Auer-Grumbach, 2008), although cases with a congenital or childhood onset have been reported (Houlden et al., 2006 Suh et al., 2014). The progression of the diseases is usually slow. As the diseases progress, the affected individuals often develop complications, such as ulcerative mutilations muscle wasting and weakness reduced motor functions and spontaneous shooting, burning, and lancinating pains (Houlden et al., 2006 Auer-Grumbach, 2008 Rotthier et al., 2010), leading to severe physical disabilities.

HSAN IA/C are caused by autosomal dominant missense mutations in two essential genes, SPTLC1 and SPTLC2 (Rotthier et al., 2012), respectively. The genes encode the two main subunits of serine palmitoyltransferase (SPT), which is the first enzyme regulating the flux of lipids in the sphingolipid (SL) biosynthesis pathway. SPT condenses palmitoyl-CoA with l -serine to produce a sphingoid base, 3-ketosphinganine, which is rapidly reduced to sphinganine (Sa). Sa can be acylated by ceramide (Cer) synthase to produce a Cer, dihydroceramide (DHCer), which can be modified further to generate more complex SLs. Alternatively, Sa can be phosphorylated and then degraded. The latter route constitutes the SL degradation pathway (Merrill, 2011 Megyeri et al., 2016) (Figure 1A).

FIGURE 1: Elevated levels of DoxSL are toxic to yeast. (A) Schematic effect of HSAN IA/C mutations on the substrate promiscuity of SPT. The blue circles highlight the hydroxyl group that is missing in DoxSL. (B–D) Effect of sphingoid bases on the growth of the indicated strains evaluated by a spot assay. Sa, sphinganine DoxSa, 1-deoxysphinganine DoxmetSa, 1-deoxymethylsphinganine DoxSB, 1-deoxysphingoid base FA-CoA, fatty acyl-CoA DHCer, dihydroceramide DoxDHCer, 1-deoxydihydroceramide DoxmetDHCer, 1-deoxymethyldihydroceramide DoxCer, 1-deoxyceramide.

SPT can also use l -alanine or glycine as a substrate, albeit at much lower efficiency, to produce atypical sphingoid bases, 1-deoxysphinganine (DoxSa) or 1-deoxymethylsphinganine (DoxmetSa), respectively. Similar to Sa, DoxSa, and DoxmetSa can also be acylated by Cer synthase to form atypical Cers, 1-deoxydihydroceramide (DoxDHCer) and 1-deoxymethyldihydroceramide (Doxmet­DHCer), respectively. In contrast to the typical SL, 1-deoxysphingolipid (DoxSL) lacks a hydroxyl group at the first carbon. Since the hydroxyl group is required for the synthesis of complex SLs and the degradation of SLs, DoxSL cannot progress in the pathway and tends to accumulate in the cell (Merrill, 2011). The mutations found in individuals with HSAN IA/C enhance the substrate promiscuity of SPT toward l -alanine and glycine (Gable et al., 2010 Penno et al., 2010), leading to increased synthesis and therefore accumulation of DoxSL, leading to HSAN IA/C (Figure 1A). How elevated levels of DoxSL perturb the physiology of the cell and how the perturbations lead to disease progression are largely unknown.

Studies in various mammalian cells showed that elevated levels of DoxSL perturb multiple components of the cell, including actin stress fibers (Cuadros et al., 2000), mitochondria (Alecu et al., 2017 Wilson et al., 2018), and lipid droplets (Marshall et al., 2014 Esaki et al., 2015). However, to which extent the perturbations affect cell viability is unknown. An inhibitor of Cer synthase, Fumonisin B1 alleviates the toxic effects of DoxSL (Sanchez et al., 2008 Zuellig et al., 2014 Guntert et al., 2016). In addition, the levels of C22–24-1-deoxyceramide (DoxCer) in blood plasma associate with the incidence and severity of neuropathy caused by paclitaxel in cancer chemotherapy (Kramer et al., 2015). These findings suggest that different species of DoxCer have different degrees of toxicity. Various pathways of DoxSL-induced cell death have been proposed, including ER stress-induced cell death (Gable et al., 2010 Alecu et al., 2017), aberrant Ca 2+ homeostasis-induced apoptosis (Wilson et al., 2018), noncanonical apoptosis (Salcedo et al., 2007), and necrosis (Zuellig et al., 2014).

In this study, we sought a comprehensive understanding of the cytotoxicity of DoxSL by genome-wide genetic screens and lipidomics. Given that elevated levels of DoxSL are toxic to various mammalian cells, worms (Hannich et al., 2017), fruit flies (Oswald et al., 2015), mice (Eichler et al., 2009), and humans, we hypothesized that elevated levels of DoxSL are toxic to all eukaryotic cells in a conserved manner. Therefore, we used the budding yeast, Saccharomyces cerevisiae (hereafter termed yeast), as a simple eukaryotic model system to reveal the principles of DoxSL toxicity and the key DoxSL-induced perturbations that lead to cell death. By making use of the fatty acyl-CoA specificity of mammalian Cer synthase, we showed that C26-DoxDHCer is more toxic than C16- or C18-DoxDHCer. Genome-wide genetic screens and lipidomics revealed the dynamics of DoxSL accumulation and DoxSL species responsible for the toxicity over the course of DoxSL accumulation. Furthermore, we showed that DoxSa accumulation leads to depletion of major membrane lipids. By standardizing the conditions of DoxSa treatment, we showed that disruption of F-actin organization, alteration of mitochondrial shape, and accumulation of hydrophobic bodies by DoxSL are not lethal under our conditions. We found that cell death coincides with a collapsed ER membrane, although we cannot rule out other possible causes of cell death. Thus, we have unraveled key principles of DoxSL cytotoxicity that can provide insights into the clinical features of HSAN IA/C.

Supporting Information

Figure S1

Plate layout and pipetting scheme. To allow for compound screening in the absence of expensive liquid handling robots, a pipetting scheme and plate layout was developed that reduces pipetting steps by using multi-channel pipettes. (A) Grandmother plate (stock plate). Most compound libraries are delivered with a plate layout as depicted in (A). Each number refers to a specific compound while N refers to the negative control (e.g. DMSO). The NINDS library used followed this layout with 13 plates à 80 compounds (20μl, 1mM stocks in DMSO). (B) Mother plates. Using multi-channel pipettes, stocks are transferred in a row to row fashion (column to row for the blue labeled wells) into 384-well plates (“mother plates” small volume reservoirs). Depending on the amount of positive controls required, controls are added to the mother plate. For 80 compounds to be tested in one experiment (9 final assay plates) we added one positive control (green well). Alternatively positive controls can be added for each plate. (C) Baby plates. Each row of the mother plate provides compounds for one final assay plate (�y plate”). First, compounds are diluted in �ughter plates” (not shown). Then, they are transferred to baby plates. Every compound is being measured in triplicate on two different substrates (e.g. Nogo-A-𹐠 vs. control). If no substrate is to be used, the amount of tested compounds per plate can be doubled.

Figure S2

Screening pipeline adaptation (e.g. for siRNA screens). Spreading assay of 3T3 cells nucleofected with siRNA. Only cells positive for siGlo (nucleofection marker) are analyzed. Next to an image based analysis of the mean areas, object based analyses using binning as well as frequency distribution plots can be employed.: (A/B) 1° and 2° object recognition as described in Figure 3 . (A) Phalloidin channel (B) Nuclei and cytoplasm outlines identified (C/D) Primary object recognition of nucleofection marker. (C) SiGlow signals are detected as 1° objects following the same principles as for DAPI stained nuclei. (D) Outlines for detected siGlow objects (green). A size threshold is applied to exclude small punctuated background signals (arrow heads). (E) Filtering of “separated” cells colocalizing with nucleofection marker. A neighbor analysis (as depicted in Figure 3 ) combined with a relate-object function is being used to identify and filter out “separated” siGlo-positive cells (red outlines). (F-H) Analysis of cytoplasm area. The KNIME pipeline was modified to allow not only for an image based (F) but also an object based analysis of the mean areas (G/H). (G) Using a binning analysis module, all objects can be categorized in bins according to their cytoplasm areas. The amount of cells (in %) is plotted against the bins (10% intervals). (H) Object data can additionally be imported into statistical software such as GraphPadPrism 6 to allow for plotting of cumulative frequency distributions. The relative frequency (in %) is plotted against the cumulated cytoplasm area (in μm 2 ). - Magnification: Calibration bars (50µm) in A are also applicable to B-E.

Figure S3

KNIME Pipeline for data normalization, hit selection and analysis. An analysis pipeline was developed in KNIME to allow for data processing. The major steps in the pipeline are annotated and color-coded including steps such as data import, outlier removal, data normalization, visualization, hit selection, pivoting and data export. A high resolution version of this file can be found in supporting File S3.

File S1

ReNamer presets file. Settings file to batch rename images and to incorporate meta tags.

File S2

CellProfiler pipeline 1. Pipeline as shown in Figure 3 (consisting of 2 parts: �itional file 2A.cp” and �itional file 2B.cp”) - to be imported into CellProfiler software package.

File S3

KNIME pipeline. Pipeline as shown in Figure 3 - to be imported into KNIME software package. Zip folder includes a folder named �itional file 3 which contains the “KNIME Pipeline – overview.pdf” (High resolution image of KNIME pipeline), the “KNIME” (Pipeline files for import into KNIME), the “Node 11 – Layout.xls” (Annotation file to be loaded into KNIME node 11), the “Shuffle Annotations.xls” (Annotation file for reshuffling).

File S4

CellProfiler pipeline 2. Pipeline as shown in Figure 2 - to be imported into CellProfiler software package.


Flavored e-liquids

Flavored e-liquids were purchased from The Vapor Girl (, NJOY (, and E-TONIC ( The e-liquids contained a variety of nicotine concentrations, ranging from 0 to 12 mg/mL, and a PG to VG ratio of 55:45. Therefore, a 55/45 PG/VG vehicle control was made in our laboratory using chemicals purchased from Sigma-Aldrich (St. Louis, MO). For more information about the e-liquids, see S1 Table.

Chemicals and reagents

PG (FG grade), VG (FG grade), and DMSO (ACS grade) were purchased from Sigma-Aldrich. Calcein-AM and propidium iodide were purchased from Thermo-Fisher (Waltham, MA). A modified Ringers solution (101 mM NaCl, 12 mM NaHCO3, 24 mM HEPES, 1.2 mM MgCl2, 1.2 mM CaCl2∙2 H2O, 5.2 mM KCl, and 10 mM D-(+)-Glucose) was made with chemicals purchased from Sigma-Aldrich (all ACS grade). Cell culture reagents were obtained from Gibco (Waltham, MA).

Cell culture

HEK239T cells were incubated at 37 °C with 5% CO2 and cultured in DMEM supplemented with 10% FBS and 1X penicillin/streptomycin. hA549 cells were incubated at 37 °C with 5% CO2 and cultured in RMPI 1640 supplemented with 10% FBS and 1X penicillin/streptomycin.

Primary HBECs and hASMCs were harvested by enzymatic digestion of human bronchial tissue obtained from donor lungs using protocols approved by the University of North Carolina at Chapel Hill Committee on the Protection of the Rights of Human Subjects. HBECs were plated on 6.5 mm Transwell T-col culture inserts (Coning, NY) and cultured at the air–liquid interface in UNC air–liquid interface media for 28 days before use as previously described [57]. hASMCs were cultured in 384-well plates, incubated at 37 °C with 5% CO2, and cultured in DMEM-α supplemented with 10% FBS and 1X penicillin/streptomycin using passages 3–6 [29].

Bronchoalveolar lavage fluid was obtained from healthy human subjects under a protocol approved by the University of North Carolina at Chapel Hill Committee on the Protection of the Rights of Human Subjects (#91–0679). All patients included in this study gave their written informed consent. Airway macrophage (AM) isolation was performed as previously described [58]. In brief, the cell pellet was resuspended in macrophage medium (RPMI 1640, 10% FBS, 100 U/ml penicillin, 100 μg/ml streptomycin). Following a 3-h adherence at 37 °C, 5% CO2, supernatants were removed, and adherent cells were washed 5 times with PBS. Cell preparations typically consisted of >98% AMs. Freshly isolated AMs were seeded onto 96-well plates at a concentration of 10,000 AMs per well and cultured in macrophage medium for the duration of the experiment.

Primary viability screen

HEK293T cells were plated on poly-L-lysine–coated 384-well plates from Corning (Corning, NY) at a density of 5,000 cells per well at t = 0 and incubated at 37 °C, 5% CO2 for 4 h to allow cells to adhere. Cells were imaged with a Cytation5 imaging plate reader (BioTek, Winooski, VT) using the bright-field feature to establish baseline surface area. After 4 h, cells were treated with e-liquids at a concentration of 1% (n = 4) and returned to the Cytation5, and images were acquired every 2 h for 24 h. Controls included PBS (negative), vehicle (10% 55:45 PG/VG, positive), and media (baseline). At t = 30–32 h, media were replaced with a modified Ringers solution containing calcein-AM (3 μM) and propidium iodide (3 μM) and incubated for 30 min to measure cell viability. The ratio of the fluorescence intensity of calcein and propidium iodide was normalized to media controls. Gen5 2.09 software (Biotek) was used to acquire bright-field images, and ImageJ (NIMH, Bethesda, MD) was used to calculate covered surface area to assess cell growth.

Secondary viability screen

HEK293T cells were plated on poly-L-lysine–coated 384-well plates (Corning, NY) at a density of 5,000 cells per well at t = 0 and incubated for 4 h to allow cells to adhere. At that time, cells were treated with various concentrations of e-liquid diluted in media for 24 h, including PBS (negative), vehicle (PG/VG, positive), and media controls. At t = 28–30 h, media were replaced with a modified Ringers solution containing calcein-AM (3 μM) and propidium iodide (3 μM) as a live/dead cell stain and incubated for 30 min. Cells were then imaged with a Cytation5 imaging plate reader (BioTek). The ratio of the fluorescence intensity of calcein and propidium iodide was normalized to media controls and plotted as 8- or 16-point dose–response curves. A nonlinear 4-parameter regression was conducted, and the LC50 value was determined for each e-liquid using GraphPad Prism6 (La Jolla, CA).

Cell line validation assay

Cells were plated on poly-L-lysine–coated 384-well plates at a density of 5,000 cells per well for A549 and 1,000 cells per well for hASMC cells at t = 0 and incubated for 4 to 6 h to allow cells to adhere. At that time, cells were treated with various concentrations of e-liquid diluted in media for 22 to 24 h, including PBS (negative), vehicle (PG/VG, positive), and media controls. At t = 28–30 h, media were replaced with a modified Ringers solution containing calcein-AM (3 μM) and propidium iodide (3 μM) as a live/dead cell stain and incubated for 30 min. Cells were then imaged with a Cytation5 imaging plate reader (BioTek). The ratio of the fluorescence intensity of calcein and propidium iodide was normalized to media controls and plotted as 8- or 16-point dose–response curves each dose was run in triplicate (n = 3) on 3 independent occasions (N = 3). A nonlinear 4-parameter regression was conducted, and the LC50 value was determined for each e-liquid (GraphPad Prism6).

Manual E-cig and aerosol generation

E-cig aerosols were generated using a Sigelei FuChai 200 W device with a Crown stainless steel subtank and a 0.25 Ω SUS316 dual coil from Uwell (City of Industry, CA). Aerosols were generated by activating the E-cig device and drawing into a 100 mL syringe from the mouthpiece of the subtank. Based on existing E-cig topography [59–61], we generated 70 mL puffs drawn over 4 s and dispensed with a flow rate of 0.84 L/min at 100 W, unless otherwise stated. To directly vape into 96-well plates, we used a 3D printed manifold as previously described [31]. These manifolds were used to simultaneously vape 6 wells per plate. Cells were exposed to 10 puffs of vaped e-liquid as indicated above. We have shown that e-liquids are autofluorescent, and using autofluorescence as an indicator of deposition, we previously found that our vaping approach in 96-well plates resulted in an even deposition of e-liquid vapor that was highly reproducible [31].

Automated E-cig vapor exposure of HBECs

HBECs were incubated apically for 20 min with PBS to remove excess mucus 24 h before exposure. On the day of exposure, cultures were loaded into the exposure block of a VC10 smoking robot (Vitrocell, Germany) with each culture insert exposed to E-cig vapor from a Sigelei Fuchai 200 W third-generation device set to 100 W, using Uwell Crown tanks with 0.25 Ω dual coils. The device was activated by a pneumatic actuator integrated into the system and connected directly to the syringe pump of the VC10 before a triangle curve puff was applied over 4 s for a volume of 70 mL and exhausted over 8 s with a period of 30 s. The vapor flowed into the 24 wells of the exposure block, with each well being fed directly by a “trumpet” allowing the vapor access to each HBEC mucosal surface. Serosally, the inserts were in contact with ALI media and were maintained at 37 °C throughout the exposure period. Cells were exposed to 70 puffs using the puff parameters described above. After the exposure, the cells were replaced in 24-well plates and returned to the 37 °C, 5% CO2 incubator for 24 h. The lines of the VC10 were also exposed to filtered compressed air to flush the majority of the vapor condensate from the lines, pump cylinder, and exposure apparatus before the next exposure with a new e-liquid, and the entire system was cleaned after each vaping session.

Aerosol validation assay

HEK293T cells were plated on poly-L-lysine–coated 96-well plates (Corning, NY) at a density of 30,000 cells per well at t = 0 and incubated for 4 to 6 h to allow cells to adhere. AMs were plated as described above. Cells were exposed to 10 puffs of vaped e-liquids using a 4 s, 70 ml puff and incubated for 22 to 24 h. Media were then replaced with a modified Ringers solution containing calcein-AM (3 μM) and propidium iodide (3 μM) and incubated for 30 min to measure viability stain. Cells were then imaged using a Cytation5 imaging plate reader (BioTek). The normalized ratio of the average fluorescence intensity of calcein and propidium iodide was reported.

O2 measurements

The PO2 was measured using a modification of our previous method [62]. In brief, the voltage output from a solid-state O2 electrode (STDO11) from Ohaus (Parsippany, NJ) was read using a pH/voltage meter (Thermo-Fisher, Waltham, MA) operating in voltage mode. The O2 electrode was calibrated using media with atmospheric O2 (i.e., approximately 21% O2), and media bubbled for 2 h with 100% N2 (i.e., 0% O2). Cell culture media ± 30% PG/VG were added to HEK293T cells for 24 h, and O2 levels were read immediately after calibration.

GC-MS analysis of e-liquids

Qualitative e-liquid analysis was performed on a Bruker EVOQ 456 gas chromatograph-triple quadrupole mass spectrometer (Billerica, MA) using an Agilent DB-5MS capillary column (30 m, 0.25 mm ID, 0.25 μM film) and helium carrier gas (99.999% purity Santa Clara, CA). Injections (1 μL) were performed using a Bruker CP-8400 autosampler with an injector temperature of 270 °C. The GC oven was programmed with a 12.5 min temperature gradient (60–250 °C), and the transfer line and EI source were held at 250 °C. Samples were prepared by diluting 50 μL of e-liquid in 1 mL of methanol (optima grade) and vortexing for 30 s. Full-scan mass spectra were acquired from m/z 40–500. Compound identification was performed using the NIST 2014 mass spectral database (Gaithersburg, MD) and AMDIS chromatography software.

For the quantitative process, flavor concentrations were determined by standard addition. E-liquids were diluted in methanol (optima grade) and quantitative standards. A full list of e-liquid dilutions and standard concentrations is given in S2 Table. Selected ion monitoring (SIM) mass spectra were acquired for each of the quantified flavors. SIM parameters are given in S3 Table. Peak areas of quantitative ions were integrated for quantification of each of the flavors. Qualitative ions were used for confirmation of compound identity.

Statistics and bioinformatics analysis of e-liquid population

All experiments were performed on a minimum of 3 separate occasions (N = 3). All data are shown as mean ± standard error, such that “n” refers to the number of plates or donors as appropriate. For 384-well–plate experiments, each dose was performed in triplicate per plate. All statistic and curve plotting were performed using Prism 6 (GraphPad, La Jolla, CA).

An ordination technique, NMDS was applied in R version 3.3.3 [63] using the package “vegan” [64] to matrices containing e-liquids and their binary (presence/absence) chemical composition. The same data table was clustered using k-modes (k = 2) using the package “klaR” [65], and chemicals within each cluster were compared using a Welch two-sample t test, in which resultant p-values were adjusted using Bonferroni correction.


Recently more and more researchers query the predictability of cytotoxicity results of biomedical Mg alloys obtained according to ISO 10993 due to significant difference between in vitro and in vivo corrosion. This study aimed to observe the influence of different extraction parameters (time, volume/surface ratio and medium composition) on cytotoxicity results and illustrate whether more predictable results could be obtained by adjusting the extraction parameters. The results showed that longer extraction time and smaller extraction volume/surface ratio improve the sensitivity of screening Mg materials by making inferior Mg materials release relatively more ions to the extract and more predictable results could not be obtained by the way of simply adding bovine serum albumin (BSA) into the extraction medium to the same level in vivo or simply using fetal bovine serum (FBS) directly as extraction medium, since BSA and FBS accelerated the corrosion of Mg materials during extraction and they affected the cells׳ health states during the test. In order to get more predictable results, in our opinions, it is necessary to establish a database of primary cells׳ hazards (metal ions, pH and H2 gas) tolerance and a set of in vitro corrosion test with high similarity in vivo, which is very difficult to realize now however.

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Development of more complex, biologically relevant, and predictive cell-based assays for compound screening is a primary challenge in drug discovery. The integration of three-dimensional (3D) assay models is becoming more widespread to drive translational biology. Higher complexity cell models have gained popularity because they better mimic in vivo environments and responses to drug treatment. Specifically, 3D cell cultures offer the advantage of closely recapitulating aspects of human tissues including the architecture, cell organization, cell-cell and cell-matrix interactions, and more physiologically-relevant diffusion characteristics. Utilization of 3D cellular assays adds value to research and screening campaigns, spanning the translational gap between 2D cell cultures and whole-animal models. By reproducing important parameters of the in vivo environment, 3D models can provide unique insight into the behavior of stem cells and developing tissues in vitro.

Enzyme-Linked Immunosorbent Assay (ELISA)

ELISA (enzyme-linked immunosorbent assay) is a method used to quantitatively detect an antigen within a sample. An antigen is a toxin or other foreign substance, for example a flu virus or environmental contaminant, that causes the vertebrate immune system to mount a defensive response. The range of potential antigens is vast, so ELISAs are used in many areas of research and testing to detect and quantify antigens in a wide variety of sample types. Cell lysates, blood samples, food items, and more can be analyzed for specific substances of interest using ELISAs. There are four major types of ELISAs: direct, indirect, competitive and sandwich. Each type is described below with a diagram illustrating how the analytes and antibodies are bonded and used. Direct ELISA In a direct ELISA, the antigen is bound to the bottom of the microplate well, and then it is bound by an antibody that is specific to the antigen and also conjugated to an enzyme or other molecule that enables detection. Indirect ELISA In an indirect ELISA, the antigen is bound to the bottom of the microplate well, then an antibody specific to the antigen is added. A secondary antibody, conjugated to an enzyme or other detection molecule, is then bound to the first antibody. Competitive ELISA In a competitive ELISA, a reference antigen is bound to the bottom of microplate wells. Sample plus antibody are added to the wells, and if there is antigen present in the sample, it competes with reference antigen for binding to the antibody. Unbound material is washed away. The more antigen was in the sample, the less antibody ends up bound to the bottom of the wells by the reference antigen, and the lower the signal. Sandwich ELISA For the sandwich ELISA, two antibodies specific to two different epitopes on the target antigen are used. The capture antibody is bound to the bottom of the microplate well and binds one epitope of the antigen. The detection antibody binds to the antigen at a different epitope and is conjugated to an enzyme that enables detection. (If the detection antibody is unconjugated, then a secondary enzyme-conjugated detection antibody is required).

Neurite Outgrowth Analysis

Neurite outgrowth is assessed by the segmentation and quantification of neuronal processes. These neuronal processes can be imaged using a fluorescence microscope and quantified with manual tracing and counting when throughput is low. However, for samples in a higher-throughput microplate format, an automated imaging system paired with analysis software is a more efficient solution. Molecular Devices offers different options for automated imagers so that labs can select a system that best fits their research. Read on to see how CellReporterXpress software can be used to more efficiently acquire and analyze neuronal cell data.

GPCRs (G protein-coupled receptors) and Ion Channels

GPCRs (G protein-coupled receptors) are the largest protein family, with between 600 and 1000 members, and have been linked to many normal biological as well as pathological conditions. They are also known as seven transmembrane (7-TM) receptors, and about 45% of modern medicinal drugs affect this target class. The function of GPCRs is highly diverse, recognizing a wide range of ligands, including photons, small molecules, and proteins. Ion channels are pores in the cellular membrane that allow ions to pass in and out of the cell. There are over 400 genes for ion channels in the human genome. Many of them have been targeted by drugs that are now blockbusters. Direct measurement of ion channel activity is measured using traditional electrophysiology equipment for patch-clamping. However, the throughput is very low. Ion channel activity can also be measured indirectly with much higher throughput by using fluophores sensitive to changes in membrane potential, calcium flux, and potassium flux. Solutions for identifying early leads against GPCRs and ion channel targets We offer a variety of assay and instrument solutions to support studies of GPCR and ion channel function including assay kits, cellular screening and imaging systems, and microplate readers.

Stem Cell Research

Stem cells provide researchers with new opportunities to study targets and pathways that are more relevant to disease processes. They offer a more realistic model to identify and confirm new drug targets and generate pharmacology and toxicology data earlier, with stronger translation to the clinical setting. Additionally, the application of stem cells in drug development creates a new path to personalized medicine, while at the same time reducing, or even potentially replacing, animal testing. Induced pluripotent stem cell-derived (iPSC-derived) cells enable researchers to study primary cells without the limitations traditionally encountered in obtaining such cells.

Protein and Nucleic Acid Detection

Our application notes demonstrate the quantitation of nucleic acids and protein in a microplate format offers higher throughput and automated calculation of results compared to other methods.

Cell Counting

The ability to accurately quantitate cell number in multi-well microplates enables a multitude of biological applications that study cell health or proliferation. These applications may make use of endpoint assays for imaging fluorescently-stained nuclei, or may demand robust transmitted light imaging of unstained live or fixed cells. In both cases, the enumeration of the cells through software segmentation should be fast and reliable. Here, we discuss the various methods and techniques used to assess proliferation, cytotoxicity, and confluence using cell counting, which can be quickly accomplished with either brightfield or fluorescent imaging using an automated imaging system and analysis software.

Patch Clamp Electrophysiology

The Patch-clamp technique is a versatile electrophysiological tool for understanding ion channel behavior. Every cell expresses ion channels, but the most common cells to study with patch-clamp techniques include neurons, muscle fibers, cardiomyocytes, and oocytes overexpressing single ion channels. To evaluate single ion channel conductance, a microelectrode forms a high resistance seal with the cellular membrane, and a patch of cell membrane containing the ion channel of interest is removed. Alternatively, while the microelectrode is sealed to the cell membrane, this small patch can be ruptured giving the electrode electrical access to the whole cell. Voltage is then applied, forming a voltage clamp, and membrane current is measured. Current clamp can also be used to measure changes in membrane voltage called membrane potential. Voltage or current change within cell membranes can be altered by applying compounds to block or open channels. These techniques enable researchers to understand how ion channels behave both in normal and disease states and how different drugs, ions, or other analytes can modify these conditions.

Cell Line Development

Stable cell lines are widely used in a number of important applications including biologics (e.g. recombinant protein and monoclonal antibody) production, drug screening, and gene functional studies. The process of developing stable cell lines often starts with transfecting selected host cells, typically CHO or HEK 293 cells, with desired plasmids. After transfection, researchers then screen and quantify high-expressing clones. Once these high producers are identified, the cell lines and/or the proteins produced by the cells are validated. The manual screening methods traditionally used for cell line development are time-consuming and labor-intensive, creating a great demand for high throughput, automated solutions for such efforts. The general workflow below helps identify the systems that can aid in your research.

Cell Imaging & Analysis

Researchers have several options in methods for imaging cells, from phase-contrast microscopy that shows intact cells to fluorescent imaging of single molecules or organelles. Cellular analysis is performed to evaluate and measure the current state of cells, such as cell integrity, toxicity, and viability and various other research applications. An integral part of cellular analysis is data collection, analysis, and export into a meaningful and useful format.