This work was funded by the EPSRC studentship (Sci-Phy-4-Health Centre for Doctoral Training L016346) to D.P., K.R. and L.F., Wellcome Trust Seed Award Grant (109604/Z/15/Z) to D.P., British Heart Foundation Grants (PG/17/55/33087, RG/17/15/33106) to D.P., European Union (grant agreement No 633196 [CATCH ME] to P.K. and L.F.), British Heart Foundation (FS/13/43/30324 to P.K. and L.F.; PG/17/30/32961 to P.K. and A.H.), and Leducq Foundation to P.K.. J.W. is supported by the British Heart Foundation (FS/16/35/31952).

<ol>
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P.K. receives research support from several drug and device companies active in atrial fibrillation and has received honoraria from several such companies. L.F. has received institutional research grants EU, BHF, MRC, DFG and Gilead.&#160;P.K. and L.F. are listed as inventors on two patents held by University of Birmingham (Atrial Fibrillation Therapy WO 2015140571, Markers for Atrial Fibrillation WO 2016012783).

All other authors declare no potential conflict of interest.

Here, we present a step-by-step guide for the utilization of open-source software ElectroMap for flexible and multi variable analysis of cardiac optical mapping datasets. For successful use of ElectroMap, imaging data is required to be in .tif or .MAT formats. ElectroMap incorporates several modifiable user settings. As demonstrated in Figure 2A, this is necessary due to the wide heterogeneity that exists between experimental models and imaging hardware. This means however that default settings within the software will not always be optimal, so a critical step in using the software is for the user to tune settings for their particular experimental setup. These include camera settings and timescales, as shown in Figure 2B. Once optimal settings have been found, these can be saved and reloaded at later times by selecting Configuration File.
Incorporation of automated CL measurement and signal segmentation are key advantages of the software. These features allow analysis of acute responses in experimental recordings and widen analysis from focusing on isolated single beats. Once desired segmentation has been achieved, the Single File Analysis module allows automated analysis of each individual segment (including single beats), realizing high-throughput analysis of multiple variables across the recording outputted in a single .csv file. In conjunction, ensemble averaging of grouped peaks is an effective method to improve quality of noisy signals that is automatically performed in ElectroMap. However, ensemble averaging is not ubiquitously beneficial, for example in studies of beat-to-beat variability. Therefore, ElectroMap integrates single beat segmentation to avoid ensemble averaging, alternative processing options to improve SNR (spatial and temporal filtering) and includes the Alternans analysis module to further investigate and map beat-to-beat variability.
Optical Mapping datasets often exhibit artifacts such as baseline drift and motion artifacts. Equally, the signals generated can be low quality due to small pixel sizes, short exposure times and low fractional fluorescent changes2. These factors prevent effective and accurate analysis of the underlying EP behavior. As outlined, ElectroMap has several processing strategies to overcome these issues. However, application of these algorithms to fundamentally poor quality/distorted data will still prevent effective analysis. SNR is therefore one of the parameters that is measured and displayed in ElectroMap. Equally, the user can select and compare the signals from specific regions from the sample using the Pixel Info and Compare modules, allowing identification of phenomena such as motion artifacts shown in Figure 5, and appropriate exclusion of data.
At present, ElectroMap does not support removal of motion artifacts from raw data in the same manner as baseline correction. Therefore, a possible future development of the software is inclusion of motion artefact removal by computational methods as has been reported31,32. Furthermore, ElectroMap is currently limited to study of one optical signal. However, for ratiometric dyes and simultaneous use of voltage and calcium dyes27, concurrent processing of two wavelength channels is required. The integration of dual signal analysis is therefore an important future addition to the software. Extension of analysis options applicable to arrhythmic datasets, such as phase singularity tracking, would equally broaden the scope of the software33,34. Finally, several of the analysis options described can also be useful in analysis of the electrode mapping data. Indeed, ElectroMap has been used to analyze electrode mapping data despite the contrasting electrogram waveform20,35, and further optimization will expand its use for this modality.

Optical mapping utilizes fluorescent reporters of voltage and/or calcium concentration to interrogate cardiac electrophysiology (EP) and calcium handling in multicellular preparations, with greater spatial resolution than achievable with traditional techniques1,2,3. Therefore, optical mapping has emerged as an important and ever increasingly utilized technique, providing key insights into physiological and pathophysiological electrical behavior in the heart3,4,5,6,7,8. Effective processing and analysis of data obtained from optical mapping experiments is complicated by several factors. The high spatiotemporal resolution nature of optical mapping datasets results in raw videos files composed of thousands of image frames, each made up of a number of individual pixels, giving rise to large data files that necessitate high-throughput and automated processing9. Small pixel sizes, poor and uneven dye loading and small fractional changes in fluorescence result in optical signals with low signal to noise ratio (SNR), requiring pre-processing before effective analysis is achievable10. Processing and analysis can be further complicated by the use of optogenetic pacing protocols which utilize light to initiate activation, potentially distorting the recorded signal from the fluorescent sensors11,12. Furthermore, once data has been processed, several non-consistent techniques and definitions can be applied to measure parameters of interest, with the most applicable techniques varying depending on experimental setup, model and question2,10,13. These limitations prevent further uptake of the technology and hinder truly objective analysis.
To overcome these limitations, several research groups have designed custom processing pipelines tailored towards their experimental model, question and hardware7,14,15,16. Others utilize commercial proprietary software where the underlying algorithms may be difficult to access4,17. As a result, there is a clear need for a freely available open-source software platform for processing and analysis of optical mapping data. It is important that this software is open-source, easy to use, flexible to parameter adjustment, applicable to a range of experimental models with distinct EP properties and crucially allows straightforward and tunable quantification of the range of cardiac parameters that can be studied using optical mapping.
We have recently published and released a comprehensive software platform, ElectroMap, for high-throughout, semi-automated processing, analysis and mapping of cardiac optical mapping datasets13. Here, we present a video manual for the utilization of ElectroMap and demonstrate how it can be used to process, analyze and map several optical mapping datasets. We focus on the use of ElectroMap to quantify standard EP and calcium handling variables and demonstrate the use of standalone conduction velocity, single file analysis and alternans modules.

<table>
	<tbody>
		<tr>
			<td>MATLAB and Simulink R2018a</td>
			<td>Mathworks, Inc, Natick, MA</td>
			<td></td>
			<td>MATLAB software</td>
		</tr>
	</tbody>
</table>

high-throughput analysis of optical mapping data using electromap

Optical mapping is an established technique for high spatio-temporal resolution study of cardiac electrophysiology in multi-cellular preparations. Here we present, in a step-by-step guide, the use of ElectroMap for analysis, quantification, and mapping of high-resolution voltage and calcium datasets acquired by optical mapping. ElectroMap analysis options cover a wide variety of key electrophysiological parameters, and the graphical user interface allows straightforward modification of pre-processing and parameter definitions, making ElectroMap applicable to a wide range of experimental models. We show how built-in pacing frequency detection and signal segmentation allows high-throughput analysis of entire experimental recordings, acute responses, and single beat-to-beat variability. Additionally, ElectroMap incorporates automated multi-beat averaging to improve signal quality of noisy datasets, and here we demonstrate how this feature can help elucidate electrophysiological changes that might otherwise go undetected when using single beat analysis. Custom modules are included within the software for detailed investigation of conduction, single file analysis, and alternans, as demonstrated here. This software platform can be used to enable and accelerate the processing, analysis, and mapping of complex cardiac electrophysiology.

All work performed as part of this study was undertaken in accordance with ethical guidelines set out by the UK Animals (Scientific Procedures) Act 1986 and Directive 2010/63/EU of the European Parliament on the protection of animals used for scientific purposes. Experiments were approved by the home office (mouse: PPL 30/2967 and PFDAAF77F, guinea pig: PPL PF75E5F7F) and the institutional review boards at University of Birmingham (mouse) and King&#8217;s College London (guinea pig). Detailed methods for collection of the raw data that has been analyzed here can be found in our previous publications5,6,14,19.
The main interface from which ElectroMap is controlled is shown in Figure 1A. The necessary steps to analyze a dataset are controlled primarily by the Load Images, Process Images, and Produce Maps buttons, and are shown highlighted in green, blue, and red, respectively in Figure 1A. Figure 1B-D shows the operations that occur on selection of each of these buttons. Load Images applies the image thresholding options as selected by the user (Figure 1B), while Process Images (Figure 1C) applies filtering and baseline correction. Finally, Produce Maps will first average data according to the time window and segmentation settings (unless single beat segmentation is chosen) and then perform analyses described above.
A key aspect of ElectroMap is its flexibility with respect to camera type and experimental model. This is crucial for the utility of an optical mapping software due to the distinct cardiac EP and anatomical characteristics that exist between widely used models. Figure 2A for example shows the action potential morphology of the murine atria when compared to the guinea pig ventricle, recorded using voltage sensitive dyes as previously reported6,14. Despite the distinct shape of the action potential, and the use of two separate optical mapping cameras with different framerates and pixel sizes, ElectroMap can be utilized to successfully analyze both datasets. However, this requires modification of some parameters within the user interface (Figure 2B). Note that the prolonged guinea pig action potential necessitates a larger time window. Additionally, to prevent top-hat baseline correction unphysiologically modifying the optically recorded signals, its time length must be increased so that it is greater than the time course of the action potential.
ElectroMap offers a multitude of processing options to help improve the SNR of optically recorded signals which may be required to effectively recover EP parameters. An example is automated ensemble averaging of peaks following data segmentation. Figure 3A-C demonstrates how the application of ensemble averaging, in lieu of other methods, can improve SNR from isolated murine left atria (n = 13). This reduces measurement heterogeneity and likelihood of analysis failure (Figure 3D). For example, a change of pacing frequency from 3 Hz to 10 Hz did not alter APD50, when no ensemble averaging is undertaken, yet an expected29 decrease in APD50 at 10 Hz pacing was observed when measured from ensemble averaged data (Figure 3E).
Figure 4 demonstrates the efficacy and utility of automated pacing frequency detection and segmentation offered by ElectroMap. Here, mouse left atria (n = 5) were paced at a 120 ms cycle length and cycle length was incrementally shortened by 10 ms until it reached 50 ms. ElectroMap automatically identified the pacing cycle length and grouped tissue averaged peaks accordingly (Figure 4A). This was achieved with high accuracy in all datasets (Figure 4B). Automated segmentation of the data allowed straightforward and high throughput analysis of the slowing of conduction velocity with increased pacing frequency/shortened cycle length (Figure 4C,D). Concurrently, APD50 (Figure 4E) and diastolic interval (Figure 4F) shortened. Amplitude of the optically measured peaks decreased, while time to peak increased (Figure 4G,H). These are again the expected restitution responses in cardiac tissue29,30 and use of ElectroMap can help therefore elucidate changes in response to pacing frequency in presence of pharmacological agents, genetic modification, or disease states.
An important consideration in the use of a software such as ElectroMap is the presence of artifacts in the underlying data. Figure 5, for example demonstrates that motion artifacts (the distortion of the optically recorded signal by tissue movement) can preclude accurate measurements of activation and especially repolarization within ElectroMap. See Discussion for further considerations.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/59663/59663fig1.jpg" /> 
Figure 1: ElectroMap main processing steps. (A) Graphical user interface of ElectroMap, with the Load Images (green), Process Images (blue), and Produce Maps (red) buttons highlighted. (B) Image thresholding options that can be applied on selecting Load Images. (C) Signal processing options available to the user include spatial and temporal filtering and baseline correction and can be applied to the image stack by pressing Process Images. (D) Ensemble averaging and parameter quantification (shown APD measurement) that is activated by selecting Produce Maps. Figure adapted from O&#8217;Shea et al., 201913. <a href="https://www.jove.com/files/ftp_upload/59663/59663fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/59663/59663fig2.jpg" /> 
Figure 2: Analysis of mouse and guinea pig data using ElectroMap. (A) Optically recorded action potential from mouse atria and guinea pig ventricles, along with both the first (df/dt) and second (d2f/dt2) derivate of these signals. The various definitions for activation and repolarization times employable within ElectroMap are highlighted. (B) Screenshots of Image and signal processing settings utilized in ElectroMaps interface. Red boxes highlight settings that required modification between analyses of mouse and guinea pig data. Figure adapted from O&#8217;Shea et al., 201913. <a href="https://www.jove.com/files/ftp_upload/59663/59663fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/59663/59663fig3.jpg" /> 
Figure 3: Ensemble averaging to resolve APD changes. (A) APD50 map and example single pixel signal from single beat optical action potentials. (B) APD50 map and example single pixel signal from optical action potentials generated by ensemble averaging of 10 successive beats (peak method). (C) SNR of single beat compared to 10 beat averaged signals. (D) APD50 heterogeneity (i) and number of measurement failures (ii) as a function of SNR for single beat and 10 beat averaged APD50 maps. (E) APD50 at 3 and 10 Hz pacing frequency, as measured from single beat and 10 beat maps. (Data shown as mean &#177; standard error, n = 13 left atria, ****p &#60; 0.001 by student&#8217;s paired t-test). <a href="https://www.jove.com/files/ftp_upload/59663/59663fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/59663/59663fig4.jpg" /> 
Figure 4: Use of ElectroMap to study pacing frequency responses in cardiac tissue. (A) Example ElectroMap screenshot of pacing frequency recognition and segmentation. (B) Comparison of known and ElectroMap measured pacing cycle lengths. (C) Activation maps at 120 ms and 60 ms pacing cycle lengths. (D-H) Grouped data of conduction velocity (D), APD50 (E), diastolic interval (F), amplitude (G), and time to peak (H) as a function of pacing cycle length decreasing from 120 ms to 60 ms in 10 ms increments. (Data shown as mean &#177; standard error, n = 5 left atria) <a href="https://www.jove.com/files/ftp_upload/59663/59663fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/59663/59663fig5.jpg" /> 
Figure 5: Effect of motion artifacts. (A) APD&#173;50 map. (B) Activation map. (C) Example signals from locations marked (crosses) on APD and activation maps. In the area of the tissue marked with the red cross, contraction has not been successfully uncoupled, distorting the measured optical signal. <a href="https://www.jove.com/files/ftp_upload/59663/59663fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about High-Throughput Analysis of Optical Mapping Data Using ElectroMap at JoVE.com

High-Throughput Analysis of Optical Mapping Data Using ElectroMap

This protocol describes the setup and use of ElectroMap, a MATLAB-based open-source software platform for analysis of cardiac optical mapping data. ElectroMap provides a versatile high-throughput tool for analysis of optical mapping voltage and calcium datasets across a wide range of cardiac experimental models.

Optical mapping is an established technique for high spatio-temporal resolution study of cardiac electrophysiology in multi-cellular preparations. Here we ...

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9.1K Views.  University of Birmingham. This protocol describes the setup and use of ElectroMap, a MATLAB-based open-source software platform for analysis of cardiac optical mapping data. ElectroMap provides a versatile high-throughput tool for analysis of optical mapping voltage and calcium datasets across a wide range of cardiac experimental models.

Video: High-Throughput Analysis of Optical Mapping Data Using ElectroMap

High-Resolution Endocardial and Epicardial Optical Mapping in a Sheep Model of Stretch-Induced Atrial Fibrillation

Atrial fibrillation (AF) is a complex cardiac arrhythmia with high morbidity and mortality.1,2 It is the most common sustained cardiac rhythm disturbance seen in clinical practice and its prevalence is expected to increase in the coming years.3 Increased intra-atrial pressure and dilatation have been long recognized to lead to AF,1,4 which highlights the relevance of using animal models and stretch to study AF dynamics. Understanding the mechanisms underlying AF requires visualization of the cardiac electrical waves with high spatial and temporal resolution. While high-temporal resolution can be achieved by conventional electrical mapping traditionally used in human electrophysiological studies, the small number of intra-atrial electrodes that can be used simultaneously limits the spatial resolution and precludes any detailed tracking of the electrical waves during the arrhythmia. The introduction of optical mapping in the early 90's enabled wide-field characterization of fibrillatory activity together with sub-millimeter spatial resolution in animal models5,6 and led to the identification of rapidly spinning electrical wave patterns (rotors) as the sources of the fibrillatory activity that may occur in the ventricles or the atria.7-9 Using combined time- and frequency-domain analyses of optical mapping it is possible to demonstrate discrete sites of high frequency periodic activity during AF, along with frequency gradients between left and right atrium. The region with fastest rotors activates at the highest frequency and drives the overall arrhythmia.10,11 The waves emanating from such rotor interact with either functional or anatomic obstacles in their path, resulting in the phenomenon of fibrillatory conduction.12 Mapping the endocardial surface of the posterior left atrium (PLA) allows the tracking of AF wave dynamics in the region with the highest rotor frequency. Importantly, the PLA is the region where intracavitary catheter-based ablative procedures are most successful terminating AF in patients,13 which underscores the relevance of studying AF dynamics from the interior of the left atrium. Here we describe a sheep model of acute stretch-induced AF, which resembles some of the characteristics of human paroxysmal AF. Epicardial mapping on the left atrium is complemented with endocardial mapping of the PLA using a dual-channel rigid borescope c-mounted to a CCD camera, which represents the most direct approach to visualize the patterns of activation in the most relevant region for AF maintenance.

This report provides a detailed description of the methodology and results of simultaneous endocardial and epicardial optical mapping of electrical excitation in the intact left atrium of a Langendorff-perfused sheep heart during stretch-induced atrial fibrillation.

 Atrial fibrillation (AF) is a complex cardiac arrhythmia with high morbidity and mortality.1,2 It is the most common sustained cardiac rhythm disturbance ...

Mouse Eye Enucleation for Remote High-throughput Phenotyping

The mouse eye is an important genetic model for the translational study of human ophthalmic disease. Blinding diseases in humans, such as macular degeneration, photoreceptor degeneration, cataract, glaucoma, retinoblastoma, and diabetic retinopathy have been recapitulated in transgenic mice.1-5 Most transgenic and knockout mice have been generated by laboratories to study non-ophthalmic diseases, but genetic conservation between organ systems suggests that many of the same genes may also play a role in ocular development and disease. Hence, these mice represent an important resource for discovering new genotype-phenotype correlations in the eye. Because these mice are scattered across the globe, it is difficult to acquire, maintain, and phenotype them in an efficient, cost-effective manner. Thus, most high-throughput ophthalmic phenotyping screens are restricted to a few locations that require on-site, ophthalmic expertise to examine eyes in live mice. 6-9 An alternative approach developed by our laboratory is a method for remote tissue-acquisition that can be used in large or small-scale surveys of transgenic mouse eyes. Standardized procedures for video-based surgical skill transfer, tissue fixation, and shipping allow any lab to collect whole eyes from mutant animals and send them for molecular and morphological phenotyping. In this video article, we present techniques to enucleate and transfer both unfixed and perfusion fixed mouse eyes for remote phenotyping analyses.

The dissection technique illustrates enucleation of the mouse eye for tissue fixation to perform phenotyping in high-throughput screens.

The mouse eye is an important genetic model for the translational study of human ophthalmic disease. Blinding diseases in humans, such as macular ...

Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence

Morphologic heterogeneity within an individual tumor is well-recognized by histopathologists in surgical practice. While this often takes the form of areas of distinct differentiation into recognized histological subtypes, or different pathological grade, often there are more subtle differences in phenotype which defy accurate classification (Figure 1). Ultimately, since morphology is dictated by the underlying molecular phenotype, areas with visible differences are likely to be accompanied by differences in the expression of proteins which orchestrate cellular function and behavior, and therefore, appearance. The significance of visible and invisible (molecular) heterogeneity for prognosis is unknown, but recent evidence suggests that, at least at the genetic level, heterogeneity exists in the primary tumor1,2, and some of these sub-clones give rise to metastatic (and therefore lethal) disease. 
Moreover, some proteins are measured as biomarkers because they are the targets of therapy (for instance ER and HER2 for tamoxifen and trastuzumab (Herceptin), respectively). If these proteins show variable expression within a tumor then therapeutic responses may also be variable. The widely used histopathologic scoring schemes for immunohistochemistry either ignore, or numerically homogenize the quantification of protein expression. Similarly, in destructive techniques, where the tumor samples are homogenized (such as gene expression profiling), quantitative information can be elucidated, but spatial information is lost. Genetic heterogeneity mapping approaches in pancreatic cancer have relied either on generation of a single cell suspension3, or on macrodissection4. A recent study has used quantum dots in order to map morphologic and molecular heterogeneity in prostate cancer tissue5, providing proof of principle that morphology and molecular mapping is feasible, but falling short of quantifying the heterogeneity. Since immunohistochemistry is, at best, only semi-quantitative and subject to intra- and inter-observer bias, more sensitive and quantitative methodologies are required in order to accurately map and quantify tissue heterogeneity in situ.
We have developed and applied an experimental and statistical methodology in order to systematically quantify the heterogeneity of protein expression in whole tissue sections of tumors, based on the Automated QUantitative Analysis (AQUA) system6. Tissue sections are labeled with specific antibodies directed against cytokeratins and targets of interest, coupled to fluorophore-labeled secondary antibodies. Slides are imaged using a whole-slide fluorescence scanner. Images are subdivided into hundreds to thousands of tiles, and each tile is then assigned an AQUA score which is a measure of protein concentration within the epithelial (tumor) component of the tissue. Heatmaps are generated to represent tissue expression of the proteins and a heterogeneity score assigned, using a statistical measure of heterogeneity originally used in ecology, based on the Simpson's biodiversity index7.
To date there have been no attempts to systematically map and quantify this variability in tandem with protein expression, in histological preparations. Here, we illustrate the first use of the method applied to ER and HER2 biomarker expression in ovarian cancer. Using this method paves the way for analyzing heterogeneity as an independent variable in studies of biomarker expression in translational studies, in order to establish the significance of heterogeneity in prognosis and prediction of responses to therapy.

Here we describe a method to quantify molecular heterogeneity in histological sections of tumor material using quantitative immunofluorescence, image analysis, and a statistical measure of heterogeneity. The method is intended for use in clinical biomarker development and analysis.

Morphologic heterogeneity within an individual tumor is well-recognized by histopathologists in surgical practice. While this often takes the form of ...

High Throughput Sequential ELISA for Validation of Biomarkers of Acute Graft-Versus-Host Disease

Unbiased discovery proteomics strategies have the potential to identify large numbers of novel biomarkers that can improve diagnostic and prognostic testing in a clinical setting and may help guide therapeutic interventions. When large numbers of candidate proteins are identified, it may be difficult to validate candidate biomarkers in a timely and efficient fashion from patient plasma samples that are event-driven, of finite volume and irreplaceable, such as at the onset of acute graft-versus-host disease (GVHD), a potentially life-threatening complication of allogeneic hematopoietic stem cell transplantation (HSCT).
Here we describe the process of performing commercially available ELISAs for six validated GVHD proteins: IL-2R&alpha;5, TNFR16, HGF7, IL-88, elafin2, and REG3&alpha;3 (also known as PAP1) in a sequential fashion to minimize freeze-thaw cycles, thawed plasma time and plasma usage. For this procedure we perform the ELISAs in sequential order as determined by sample dilution factor as established in our laboratory using manufacturer ELISA kits and protocols with minor adjustments to facilitate optimal sequential ELISA performance. The resulting plasma biomarker concentrations can then be compiled and analyzed for significant findings within a patient cohort. While these biomarkers are currently for research purposes only, their incorporation into clinical care is currently being investigated in clinical trials.
This technique can be applied to perform ELISAs for multiple proteins/cytokines of interest on the same sample(s) provided the samples do not need to be mixed with other reagents. If ELISA kits do not come with pre-coated plates, 96-well half-well plates or 384-well plates can be used to further minimize use of samples/reagents.

High throughput validation of multiple candidate biomarkers can be performed by sequential ELISA in order to minimize freeze/thaw cycles and use of precious plasma samples. Here, we demonstrate how to sequentially perform ELISAs for six different validated plasma biomarkers1-3 of graft-versus-host disease (GVHD)4 on the same plasma sample.

Unbiased discovery proteomics strategies have  the potential to identify large numbers of novel biomarkers that can improve  diagnostic and prognostic ...

High Throughput Characterization of Adult Stem Cells Engineered for Delivery of Therapeutic Factors for Neuroprotective Strategies

Mesenchymal stem cells (MSCs) derived from bone marrow are a powerful cellular resource and have been used in numerous studies as potential candidates to develop strategies for treating a variety of diseases. The purpose of this study was to develop and characterize MSCs as cellular vehicles engineered for delivery of therapeutic factors as part of a neuroprotective strategy for rescuing the damaged or diseased nervous system. In this study we used mouse MSCs that were genetically modified using lentiviral vectors, which encoded brain-derived neurotrophic factor (BDNF) or glial cell-derived neurotrophic factor (GDNF), together with green fluorescent protein (GFP). 
Before proceeding with in vivo transplant studies it was important to characterize the engineered cells to determine whether or not the genetic modification altered aspects of normal cell behavior. Different culture substrates were examined for their ability to support cell adhesion, proliferation, survival, and cell migration of the four subpopulations of engineered MSCs. High content screening (HCS) was conducted and image analysis performed. 
Substrates examined included: poly-L-lysine, fibronectin, collagen type I, laminin, entactin-collagen IV-laminin (ECL). Ki67 immunolabeling was used to investigate cell proliferation and Propidium Iodide staining was used to investigate cell viability. Time-lapse imaging was conducted using a transmitted light/environmental chamber system on the high content screening system.
Our results demonstrated that the different subpopulations of the genetically modified MSCs displayed similar behaviors that were in general comparable to that of the original, non-modified MSCs. The influence of different culture substrates on cell growth and cell migration was not dramatically different between groups comparing the different MSC subtypes, as well as culture substrates. 
This study provides an experimental strategy to rapidly characterize engineered stem cells and their behaviors before their application in long-term in vivo transplant studies for nervous system rescue and repair.

This study describes an experimental platform to rapidly characterize engineered stem cells and their behaviors before their application in long-term in vivo transplant studies for nervous system rescue and repair.

Mesenchymal stem cells (MSCs) derived from bone marrow are a powerful cellular resource and have been used in numerous studies as potential candidates to ...

An Organotypic High Throughput System for Characterization of Drug Sensitivity of Primary Multiple Myeloma Cells

In this work we describe a novel approach that combines ex vivo drug sensitivity assays and digital image analysis to estimate chemosensitivity and heterogeneity of patient-derived multiple myeloma (MM) cells. This approach consists in seeding primary MM cells freshly extracted from bone marrow aspirates into microfluidic chambers implemented in multi-well plates, each consisting of a reconstruction of the bone marrow microenvironment, including extracellular matrix (collagen or basement membrane matrix) and stroma (patient-derived mesenchymal stem cells) or human-derived endothelial cells (HUVECs). The chambers are drugged with different agents and concentrations, and are imaged sequentially for 96 hr through bright field microscopy, in a motorized microscope equipped with a digital camera. Digital image analysis software detects live and dead cells from presence or absence of membrane motion, and generates curves of change in viability as a function of drug concentration and exposure time. We use a computational model to determine the parameters of chemosensitivity of the tumor population to each drug, as well as the number of sub-populations present as a measure of tumor heterogeneity. These patient-tailored models can then be used to simulate therapeutic regimens and estimate clinical response.

We describe a high-throughput drug sensitivity assay for primary multiple myeloma cells. It consists of a reconstruction of the bone marrow microenvironment (including extracellular matrix and stroma) in multi-well plates, and a non-invasive method for longitudinal quantification of cell viability.

In this work we describe a novel approach that combines ex vivo drug sensitivity assays and digital image analysis to estimate chemosensitivity and ...

Optimized LC-MS/MS Method for the High-throughput Analysis of Clinical Samples of Ivacaftor, Its Major Metabolites, and Lumacaftor in Biological Fluids of Cystic Fibrosis Patients

Defects in the cystic fibrosis trans-membrane conductance regulator (CFTR) are the cause of cystic fibrosis (CF), a disease with life-threatening pulmonary manifestations. Ivacaftor (IVA) and ivacaftor-lumacaftor (LUMA) combination are two new breakthrough CF drugs that directly modulate the activity and trafficking of the defective CFTR-protein. However, there is still a dearth of understanding on pharmacokinetic/pharmacodynamic parameters and the pharmacology of ivacaftor and lumacaftor. The HPLC-MS technique for the simultaneous analysis of the concentrations of ivacaftor, hydroxymethyl-ivacaftor, ivacaftor-carboxylate, and lumacaftor in biological fluids in patients receiving standard ivacaftor or ivacaftor-lumacaftor combination therapy has previously been developed by our group and partially validated to FDA standards. However, to allow the high-throughput analysis of a larger number of patient samples, our group has optimized the reported method through the use of a smaller pore size reverse-phase chromatography column (2.6 &#181;m, C8 100 &#197;; 50 x 2.1 mm) and a gradient solvent system (0-1 min: 40% B; 1-2 min: 40-70% B; 2-2.7 min: held at 70% B; 2.7-2.8 min: 70-90% B; 2.8-4.0 min: 90% B washing; 4.0-4.1 min: 90-40% B; 4.1-6.0 min: held at 40% B) instead of an isocratic elution. The goal of this study was to reduce the HPLC-MS analysis time per sample dramatically from ~15 min to only 6 min per sample, which is essential for the analysis of a large amount of patient samples. This expedient method will be of considerable utility for studies into the exposure-response relationships of these breakthrough CF drugs.

Ivacaftor and ivacaftor-lumacaftor combination are two new CF drugs. However, there is still a dearth of understanding on their PK/PD and pharmacology. We present an optimized HPLC-MS technique for the simultaneous analysis of ivacaftor and its major metabolites, and lumacaftor.

Defects in the cystic fibrosis trans-membrane conductance regulator (CFTR) are the cause of cystic fibrosis (CF), a disease with life-threatening ...

Electrophysiological Assessment of Murine Atria with High-Resolution Optical Mapping

Recent genome-wide association studies targeting atrial fibrillation (AF) have indicated a strong association between the genotype and electrophysiological phenotype in the atria. That encourages us to utilize a genetically-engineered mouse model to elucidate the mechanism of AF. However, it is difficult to evaluate the electrophysiological properties in murine atria due to their small size. This protocol describes the electrophysiological evaluation of atria using an optical mapping system with a high temporal and spatial resolution in Langendorff perfused murine hearts. The optical mapping system is assembled with dual high-speed complementary metal oxide semiconductor cameras and high magnification objective lenses, to detect the fluorescence of a voltage-sensitive dye and Ca2+ indicator. To focus on the assessment of murine atria, optical mapping is performed with an area of 2 mm &#215; 2 mm or 10 mm x 10 mm, with a 100 &#215; 100 resolution (20 &#181;m/pixel or 100 &#181;m/pixel) and sampling rate of up to 10 kHz (0.1 ms) at maximum. A 1-French size quadripolar electrode pacing catheter is placed into the right atrium through the superior vena cava avoiding any mechanical damage to the atrium, and pacing stimulation is delivered through the catheter. An electrophysiological study is performed with programmed stimulation including constant pacing, burst pacing, and up to triple extrastimuli pacing. Under a spontaneous or pacing rhythm, the optical mapping recorded the action potential duration, activation map, conduction velocity, and Ca2+ transient individually in the right and left atria. In addition, the programmed stimulation also determines the inducibility of atrial tachyarrhythmias. Precise activation mapping is performed to identify the propagation of the excitation in the atrium during an induced atrial tachyarrhythmia. Optical mapping with a specialized setting enables a thorough electrophysiological evaluation of the atrium in murine pathological models.

This protocol describes the electrophysiological evaluation of murine atria utilizing an optical mapping system with a high temporal and spatial resolution, including dual recordings of the membrane voltage and Ca2+ transient under programmed stimulation through a specialized electrode catheter.

Recent genome-wide association studies targeting atrial fibrillation (AF) have indicated a strong association between the genotype and ...

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Literature databases (i.e., PubMed, Scopus, and Web of Science) differ in terms of their coverage, focus, and the tool they provide. PubMed focuses mainly on life sciences and biomedical disciplines, whereas Scopus and Web of Science are multidisciplinary. The protocol described in the current study was used to search for publications from Jordanian authors in the years 2013-2017. In this protocol, how to use each database to conduct this type of search is explained in detail. A Scopus search resulted in the highest number of documents (11,444 documents), followed by a Web of Science search (10,943 documents). PubMed resulted in a smaller number of documents due to its narrower scope and coverage (4,363 documents). The results also show a yearly trend in: (1) the number of publications, (2) the disciplines that have the most publications, (3) the countries of collaboration, and (4) the number of open access publications. In contrast, PubMed has a sophisticated keyword optimization service (i.e., Medical Subject Heading, or MeSH), while both Scopus and Web of Science provide search analysis tools that can produce representative figures. Finally, the features of each database are explained in detail and several indices that can be extracted using the search results are provided. This study provides a base for using literature databases for bibliometric analysis.

Literature databases are commonly used to assess publications in a certain subject, discipline, country, or region of the world, a practice known as bibliometric analysis. The current protocol details how to use PubMed, Scopus, and Web of Science databases to do bibliometric analysis.

Literature databases (i.e., PubMed, Scopus, and Web of Science) differ in terms of their coverage, focus, and the tool they provide. PubMed focuses mainly ...

High-throughput Nitrobenzoxadiazole-labeled Cholesterol Efflux Assay

Atherosclerosis leads to cardiovascular disease (CVD). It is still unclear whether cholesterol-HDL (cHDL) concentration plays a causal role in atherosclerosis development. However, an important factor in early stages of atheroma plaque formation is cholesterol efflux capacity to HDL (the ability of HDL particles to accept cholesterol from macrophages) in order to avoid foam cell formation. This is a key step in avoiding the accumulation of cholesterol in the endothelium and a part of reverse cholesterol transport (RCT) to eliminate cholesterol through the liver. Cholesterol efflux capacity to serum or plasma in macrophage cell models is a promising tool that can be used as biomarker for atherosclerosis. Traditionally, [3H]-cholesterol has been used in cholesterol efflux assays. In this study, we aim to develop a safer and faster strategy using fluorescent labelled-cholesterol (NBD-cholesterol) in a cellular assay to trace the cholesterol uptake and efflux process in THP-1-derived macrophages. Finally, we optimize and standardize the NBD-cholesterol efflux method and develop a high-throughput analysis using 96-well plates.

Measurement of in vitro cholesterol efflux capacity to serum or plasma in macrophage cell models is a promising tool as a biomarker for atherosclerosis. In the present study, we optimize and standardize a fluorescent NBD-cholesterol efflux method and develop a high-throughput analysis using 96-well plates.