Name: outer-boundary assisted segmentation and quantification of trabecular bones by an imagej plugin
Uploaded: 2018-03-14T14:00:00
Description: Watch this Scientific Journal Video about Outer-Boundary Assisted Segmentation and Quantification of Trabecular Bones by an Imagej Plugin at JoVE.com

This work was partially supported by grant NFSC 81170806. The authors would like to thank the micro-CT core facility of School of Stomatology, Wuhan University for helping scan and analyze the rat femurs.

Procedures involving animal subjects were conducted in accordance with the Guide for the Care and Use of Laboratory Animals (NIH publication, 8th edition, 2011), and have been reviewed and approved by the Institutional Animal Care and Use Committee of Wuhan University.
1. Software Installation
<ol>
	<li>Install ImageJ software. Download the Windows version of the ImageJ (version 1.51p) software bundled with 64-bit Java from https://imagej.nih.gov/ij/. Extract the downloaded software into a f...

<ol>
	<li>Ruegsegger, P., Koller, B., Muller, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+microtomographic+system+for+the+nondestructive+evaluation+of+bone+architecture.">A microtomographic system for the nondestructive evaluation of bone architecture.</a> Calcif Tissue Int. 58 (1), 24-29 (1996).</li><li>Muller, R., Ruegsegger, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Micro-tomographic+imaging+for+the+nondestructive+evaluation+of+trabecular+bone+architecture.">Micro-tomographic imaging for the nondestructive evaluation of trabecular bone architecture.</a> Stud Health Technol Inform. 40, 61-79 (1997).</li><li>Clark, D. P., Badea, C. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Micro-CT+of+rodents:+state-of-the-art+and+future+perspectives.">Micro-CT of rodents: state-of-the-art and future perspectives.</a> Phys Med. 30 (6), 619-634 (2014).</li><li>Bart, Z., Wallace, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microcomputed+Tomography+Applications+in+Bone+and+Mineral+Research.">Microcomputed Tomography Applications in Bone and Mineral Research.</a> Advances in Computed Tomography. 2, 121-127 (2013).</li><li>Ji, Y., Ke, Y., Gao, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Intermittent+activation+of+notch+signaling+promotes+bone+formation.">Intermittent activation of notch signaling promotes bone formation.</a> Am J Transl Res. 9 (6), 2933-2944 (2017).</li><li>Jiang, Y., Zhao, J., White, D. L., Genant, H. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Micro+CT+and+Micro+MR+imaging+of+3D+architecture+of+animal+skeleton.">Micro CT and Micro MR imaging of 3D architecture of animal skeleton.</a> J Musculoskelet Neuronal Interact. 1 (1), 45-51 (2000).</li><li>Laib, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=3D+micro-computed+tomography+of+trabecular+and+cortical+bone+architecture+with+application+to+a+rat+model+of+immobilisation+osteoporosis.">3D micro-computed tomography of trabecular and cortical bone architecture with application to a rat model of immobilisation osteoporosis.</a> Med Biol Eng Comput. 38 (3), 326-332 (2000).</li><li>Cole, H. A., Ichikawa, J., Colvin, D. C., O'Rear, L., Schoenecker, J. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantifying+intra-osseous+growth+of+osteosarcoma+in+a+murine+model+with+radiographic+analysis.">Quantifying intra-osseous growth of osteosarcoma in a murine model with radiographic analysis.</a> J Orthop Res. 29 (12), 1957-1962 (2011).</li><li>Jensen, M. M., Jorgensen, J. T., Binderup, T., Kjaer, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tumor+volume+in+subcutaneous+mouse+xenografts+measured+by+microCT+is+more+accurate+and+reproducible+than+determined+by+18F-FDG-microPET+or+external+caliper.">Tumor volume in subcutaneous mouse xenografts measured by microCT is more accurate and reproducible than determined by 18F-FDG-microPET or external caliper.</a> BMC Med Imaging. 8, 16 (2008).</li><li>Soviero, V. M., Leal, S. C., Silva, R. C., Azevedo, R. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Validity+of+MicroCT+for+in+vitro+detection+of+proximal+carious+lesions+in+primary+molars.">Validity of MicroCT for in vitro detection of proximal carious lesions in primary molars.</a> J Dent. 40 (1), 35-40 (2012).</li><li>Kohler, T., Stauber, M., Donahue, L. R., Muller, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+compartmental+analysis+for+high-throughput+skeletal+phenotyping+in+femora+of+genetic+mouse+models.">Automated compartmental analysis for high-throughput skeletal phenotyping in femora of genetic mouse models.</a> Bone. 41 (4), 659-667 (2007).</li><li>Buie, H. R., Campbell, G. M., Klinck, R. J., MacNeil, J. A., Boyd, S. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automatic+segmentation+of+cortical+and+trabecular+compartments+based+on+a+dual+threshold+technique+for+in+vivo+micro-CT+bone+analysis.">Automatic segmentation of cortical and trabecular compartments based on a dual threshold technique for in vivo micro-CT bone analysis.</a> Bone. 41 (4), 505-515 (2007).</li><li>Dougherty, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+CT+in+the+measurement+of+bone+quantity+and+bone+quality+for+assessing+osteoporosis.">Quantitative CT in the measurement of bone quantity and bone quality for assessing osteoporosis.</a> Med Eng Phys. 18 (7), 557-568 (1996).</li><li>Doube, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=BoneJ:+Free+and+extensible+bone+image+analysis+in+ImageJ.">BoneJ: Free and extensible bone image analysis in ImageJ.</a> Bone. 47 (6), 1076-1079 (2010).</li><li>Bouxsein, M. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Guidelines+for+assessment+of+bone+microstructure+in+rodents+using+micro-computed+tomography.">Guidelines for assessment of bone microstructure in rodents using micro-computed tomography.</a> J Bone Miner Res. 25 (7), 1468-1486 (2010).</li></ol>

This study describes an ImageJ plugin for analyzing trabecular bones, which is automatic, efficient, and user friendly. The plugin can also be used to quantify any 2D or 3D object for layer-by-layer measures of areas, volumes, and thicknesses. Currently, only a single measured value for each trabecular parameter is reported for each sample by standard micro-CT analysis, which cannot fully represent the characteristics of the measured entity in the selected analyzing region. The described plugin reports layer-by-layer qua...

Micro-CT analysis of trabecular bones is the standard approach for tracking morphological changes of the bones in small animals under different bone loss conditions1,2,3, where several variables related to the structures of the bones are reported4. However, such parameters are not evenly distributed in the metaphysis of long bones5, and only a summarized or averaged value is reported for each structural variable of each sample by current commercial micro-CT machines6,7, though a single value cannot fully represent the characteristics of the measured parameter in the analyzing region. Layer-by-layer quantification of trabecular bones not only retains more information for each variable, but also enables the profiling of the distributions of such variables in the analyzing region, facilitating subsequent statistical analysis of structural changes under different conditions5. Therefore, the goal of this method is quantifying trabecular bones of micro-CT scans at each slice level, which is not available in any commercially available micro-CT analysis package currently.
To efficiently segment trabecular bones slice-by-slice, automatic segmentation methods are desirable. However, the current standard technique for micro-CT analysis is based on manual interactive contouring followed by semiautomatic interpolation to separate trabecular bones from the cortical compartments, which is labor intensive, error-prone, and associated with substantial operator bias8,9,10. Automatic segmentation methods11,12 were reported, but such methods are only optimal in regions with good separation between trabecular bones and cortical bones, but not in regions without clear separations. Moreover, different segmentation parameters are required for different samples12, and it is tedious to manually select satisfactory segmentation parameters applicable to groups of bone samples by trying various parameter combinations12, even though the segmentation process is automatic when all related parameters are set. As the bone outer boundary has the greatest contrast with the scanning background and the metaphyseal cortical shells of long bones show few changes in the chosen analyzing region, segmentation methods according to the outer-boundary contour of long bones can reliably and accurately separate trabecular bones from cortical shells. The advantage of such a segmentation method is that the segmentation is based on the difference between the background and the bone&#39;s outer boundary, but not on the differences between trabecular and cortical bones6,12,13, therefore it is generally easy to find a combination of segmentation parameters that is satisfactory for a group of bone samples, facilitating more reliable analysis of trabecular changes between different groups.
At each slice level, area, perimeter, and two-dimensional (2D) thickness are reported for 2D analysis, while volume, surface, and three-dimensional (3D) thickness are reported in 3D quantifications. Such information is generally not reported by current image analysis tools, indicating that the reported procedures can be applied to general images where such information is desired.

<table border="0" cellpadding="0" cellspacing="0" style="width:595px;" width="595">
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		<col />
		<col />
		<col />
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	</colgroup>
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">ImageJ</td>
			<td style="width:93px;">NIH</td>
			<td style="width:119px;">imagej</td>
			<td style="width:167px;">Any version with a java 1.8 run time</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">trabecular analysis plugin</td>
			<td style="width:93px;">Bomomics</td>
			<td style="width:119px;">bomomics</td>
			<td>free or commercial version</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Micro CT scanner</td>
			<td style="width:93px;">Scanco</td>
			<td style="width:119px;">&#956;-50</td>
			<td>micro CT from any vendor</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Computer System</td>
			<td style="width:93px;">Lenovo</td>
			<td style="width:119px;"></td>
			<td>any brand</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Windows Operating System</td>
			<td style="width:93px;">Microsoft</td>
			<td style="width:119px;">Windows 7 x64</td>
			<td>any 64-bit Windows operating system&#160;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Office Software</td>
			<td style="width:93px;">Microsoft</td>
			<td style="width:119px;">Office 2010</td>
			<td>any speadsheet software that has xy chart function</td>
		</tr>
	</tbody>
</table>

outer-boundary assisted segmentation and quantification of trabecular bones by an imagej plugin

Micro-computed tomography (micro-CT) is routinely used to assess bone quantity and trabecular microstructural properties in small animals under different bone loss conditions. However, the standard approach for trabecular analysis of micro-CT images is slice-by-slice semi-automatic hand-contouring, which is labor intensive and error prone. Described here is an efficient method for automatic segmentation of trabecular bones according to the bone's outer boundaries, where trabecular bones can be identified and segmented automatically with accuracy with less operator bias when appropriate segmentation parameters are set. To profile satisfactory segmentation parameters, an image stack of segmentation results is displayed, where all possible combinations of the segmentation parameters are changed one by one in sequence, and segmentation results with associated parameters can easily be visually checked. As a quality-control feature of the plugin, simulated standard objects are quantified where the measured quantities can be compared with theoretical values. Layer-by-layer quantification of trabecular properties and trabecular thicknesses are reported by such a plugin, and the distributions of such properties within the selected regions can be profiled easily. Although layer-by-layer quantification retains more information about trabecular bones and facilitates further statistical analysis of structural changes, such measures are unavailable from the output of current commercial software, where only a single quantified value for each parameter is reported for each sample. Therefore, the described workflows are better approaches for analyzing trabecular bones with accuracy and efficiency.

The trabecular analysis plugin is designed to automatically segment and quantify trabecular bones with accuracy. Initially, bone outer boundary is detected and delineated followed by a hole-filling operation where any holes within bone outer cortical shells are filled. Then an erosion operation is performed to exclude the outer cortical bones and get the segmented trabecular bones. Finally, measures of trabecular bones in the segmented region are quantified.
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Watch this Scientific Journal Video about Outer-Boundary Assisted Segmentation and Quantification of Trabecular Bones by an Imagej Plugin at JoVE.com

Outer-Boundary Assisted Segmentation and Quantification of Trabecular Bones by an Imagej Plugin

We present a workflow for segmenting and quantifying trabecular bones for 2D and 3D images based on the bone&#39;s outer boundary using an ImageJ plugin. This approach is more efficient and accurate than the current manual hand-contouring approach, and provides layer-by-layer quantifications, which are not available in current commercial software.

Micro-computed tomography (micro-CT) is routinely used to assess bone quantity and trabecular microstructural properties in small animals under different ...

The overall goal of this procedure is to quantify structural measurements of trabecular bones automatically with accuracy and efficiency. This method can help answer key questions in the image analysis field, such as how to measure irregular structures accurately with efficiency. The main advantage of this technique is that structural measurements of two-dimensional or three-dimensional objects by such a technique are more accurate and efficient than the current available quantification approaches.To begin this procedure, first install the ImageJ software and trabecular analysis plugins, as outlined in the text protocol. Open the ImageJ software. Under Plugins, BoMomics, Simulate Objects, click the Circle button.In the resulting popup window, enter 200 as the diameter, and then click OK to generate a simulated circle with a diameter of 200 pixels. Save the generated circle in TIFF format. Next, in Plugins, BoMomics, Simulate Objects, click the Square button.In the popup, enter 200 and the side length, and click OK to generate a simulated square with a side length of 200 pixels. Save it in TIFF format. Then, in the same menu, click the Sphere button.Enter 30 as the diameter, and click OK to generate the simulated sphere. Click the Plugins, 3D, Volume Viewer to view the sphere, and save it in TIFF format. Finally, in Plugins, BoMomics, Simulate Objects, click the Cylinder button.Enter 30 as the diameter and 100 as the height, and then click OK to generate the simulated cylinder. After this, click Plugins, 3D, Volume Viewer to view the cylinder, and save it in TIFF format. First, open the ImageJ software, and open or import a scanned image.Slide the bottom scroll bar to choose a slice, and then click the Image, Adjust, Threshold button. In the Threshold popup window, adjust the minimum and maximum threshold values to ensure that the bones are well separated from the background. Record the minimal threshold value as the cortical bone threshold value.Next, click the Plugins, BoMomics, Trabecular Parameter Profiling button. In the popup window, set the Slice Index to the position of the representative slice. Set the Cortical Bone, Range, and Step values to calculate a set of cortical thresholds for profiling segmentation parameters.After this, set the Noise Diameter, Step, and Range values to specify a set of noise values for the analysis. Set the Hole Diameter, Step, and Range values for calculating a set of hole values. Click OK to perform the parameter profiling.In the Parameter Profiling Results window, visually check the segmentation results, and select a slice layer where the bone's outer boundary is outlined accurately. Then, retrieve the profiling parameters from the corresponding entry in the Parameter Profiling Results table. To begin analyzing the trabecular bones, open the ImageJ software and open or import a scanned image.Click the Plugins, BoMomics, Trabecular Segmentation button. Fill in appropriate analysis parameters, as shown here. Next, click OK to perform the trabecular segmentation.Visually inspect the results in the Trabecular Segmentation Results window. Then, save the extracted trabecular bones shown in the Segmented Trabecular Bones window in TIFF format for further analysis. After this, click the Plugins, BoMomics, Trabecular Analysis button, and fill in the appropriate analysis parameters, as outlined in the text protocol.In the Results Reporting section, select one or more parameters to be measured where the options are trabecular bone volume, total volume, and thickness measured either two-dimensionally or three-dimensionally. To perform trabecular analysis, select the checkboxes for both 2D and 3D, and then click OK.To begin quantifying objects, open a simulated image in the ImageJ software. Select the Plugins, BoMomics, Trabecular Analysis button, and fill in the appropriate analysis parameters, keeping the default values for Start, End, Outline Boundary, and Trabecular Bones, while setting Noise Reduction Diameter, Hole Filling Diameter, and Cortical Thickness Diameter to zero.In the Results Reporting section, select both 2D and 3D as the parameters to be measured. Then, click OK to perform trabecular analysis on the simulated object. After this, calculate the calibrated bone volume, total volume, bone mineral content, bone volume fraction, and bone mineral density in spreadsheet columns, and analyze the data, as outlined in the text protocol.In this study, an ImageJ plugin is used to automatically segment and quantify trabecular bones. Representative parameter profiling analysis using different parameter conditions reveals that some combinations are more accurate when delineating a bone's outer boundaries than others. Next, segmentation and analysis is performed to quantify measurements of the trabecular bones.The results of this segmentation can be visually checked slice-by-slice. The raw quantifications of the bone volume, the total volume, the sum of gray values, and the thickness, either in two or three dimensions, can be reported depending on which options are selected during analysis. The calibration information is extracted from the scanned micro-CT dataset, and calibrated measurements of bone volume, total volume, bone mineral content, bone volume fraction, and bone mineral density are then calculated.Their distributions can then be profiled in the selected analyzing region, layer-by-layer, against the layer positions. Once mastered, this technique can quantify trabecular bones of 500 image layers in 10 to 20 minutes if it's performed properly. We first had the idea for this method when we found that the results reported by the micro-CT vendor software were not reproducible when the same dataset was analyzed by the same experienced operator.After watching this video, you should have a good understanding of how to choose appropriate bone segmentation parameters and perform analysis of long bones with minimal user interactions.

outer-boundary-assisted-segmentation-quantification-trabecular-bones

Research

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Bioengineering

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In order to mimic cell membranes, the supported lipid bilayer (SLB) is an attractive platform which enables in vitro investigation of membrane-related processes while conferring biocompatibility and biofunctionality to solid substrates. The spontaneous adsorption and rupture of phospholipid vesicles is the most commonly used method to form SLBs. However, under physiological conditions, vesicle fusion (VF) is limited to only a subset of lipid compositions and solid supports. Here, we describe a one-step general procedure called the solvent-assisted lipid bilayer (SALB) formation method in order to form SLBs which does not require vesicles. The SALB method involves the deposition of lipid molecules onto a solid surface in the presence of water-miscible organic solvents (e.g., isopropanol) and subsequent solvent-exchange with aqueous buffer solution in order to trigger SLB formation. The continuous solvent exchange step enables application of the method in a flow-through configuration suitable for monitoring bilayer formation and subsequent alterations using a wide range of surface-sensitive biosensors. The SALB method can be used to fabricate SLBs on a wide range of hydrophilic solid surfaces, including those which are intractable to vesicle fusion. In addition, it enables fabrication of SLBs composed of lipid compositions which cannot be prepared using the vesicle fusion method. Herein, we compare results obtained with the SALB and conventional vesicle fusion methods on two illustrative hydrophilic surfaces, silicon dioxide and gold. To optimize the experimental conditions for preparation of high quality bilayers prepared via the SALB method, the effect of various parameters, including the type of organic solvent in the deposition step, the rate of solvent exchange, and the lipid concentration is discussed along with troubleshooting tips. Formation of supported membranes containing high fractions of cholesterol is also demonstrated with the SALB method, highlighting the technical capabilities of the SALB technique for a wide range of membrane configurations.

Biomembrane Fabrication by the Solvent-assisted Lipid Bilayer SALB Method

We present an experimental protocol to form a supported lipid bilayer on solid substrates without using lipid vesicles. We demonstrate a one-step method to form a lipid bilayer on silicon dioxide and gold as well as supported membranes with cholesterol-enriched domain for various biological applications.

In order to mimic cell membranes, the supported lipid bilayer (SLB) is an attractive platform which enables in vitro investigation of membrane-related ...

Whole-body Mass Spectrometry Imaging by Infrared Matrix-assisted Laser Desorption Electrospray Ionization (IR-MALDESI)

Ambient ionization sources for mass spectrometry (MS) have been the subject of much interest in the past decade. Matrix-assisted laser desorption electrospray ionization (MALDESI) is an example of such methods, where features of matrix-assisted laser desorption/ionization (MALDI) (e.g., pulsed nature of desorption) and electrospray ionization (ESI) (e.g., soft-ionization) are combined. One of the major advantages of MALDESI is its inherent versatility. In MALDESI experiments, an ultraviolet (UV) or infrared (IR) laser can be used to resonantly excite an endogenous or exogenous matrix. The choice of matrix is not analyte dependent, and depends solely on the laser wavelength used for excitation. In IR-MALDESI experiments, a thin layer of ice is deposited on the sample surface as an energy-absorbing matrix. The IR-MALDESI source geometry has been optimized using statistical design of experiments (DOE) for analysis of liquid samples as well as biological tissue specimens. Furthermore, a robust IR-MALDESI imaging source has been developed, where a tunable mid-IR laser is synchronized with a computer controlled XY translational stage and a high resolving power mass spectrometer. A custom graphical user interface (GUI) allows user selection of the repetition rate of the laser, number of shots per voxel, step-size of the sample stage, and the delay between the desorption and scan events for the source. IR-MALDESI has been used in variety of applications such as forensic analysis of fibers and dyes and MSI of biological tissue sections. Distribution of different analytes ranging from endogenous metabolites to exogenous xenobiotics within tissue sections can be measured and quantified using this technique. The protocol presented in this manuscript describes major steps necessary for IR-MALDESI MSI of whole-body tissue sections.

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Ambient ionization sources for mass spectrometry (MS) have been the subject of much interest in the past decade. Matrix-assisted laser desorption ...

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A Novel Surgical Technique As a Foundation for In Vivo Partial Liver Engineering in Rat

We establish a novel surgical technique for an in vivo single liver lobe perfusion model in rat as a prerequisite for further studying in vivo partial liver engineering in the future.

Organ engineering is a novel strategy to generate liver organ substitutes that can potentially be used in transplantation. Recently, in vivo liver ...

Detection of Endotoxin in Nano-formulations Using Limulus Amoebocyte Lysate (LAL) Assays

When present in pharmaceutical products, a Gram-negative bacterial cell wall component endotoxin (often also called lipopolysaccharide) can cause inflammation, fever, hypo- or hypertension, and, in extreme cases, can lead to tissue and organ damage that may become fatal. The amounts of endotoxin in pharmaceutical products, therefore, are strictly regulated. Among the methods available for endotoxin detection and quantification, the Limulus Amoebocyte Lysate (LAL) assay is commonly used worldwide. While any pharmaceutical product can interfere with the LAL assay, nano-formulations represent a particular challenge due to their complexity. The purpose of this paper is to provide a practical guide to researchers inexperienced in estimating endotoxins in engineered nanomaterials and nanoparticle-formulated drugs. Herein, practical recommendations for performing three LAL formats including turbidity, chromogenic and gel-clot assays are discussed. These assays can be used to determine endotoxin contamination in nanotechnology-based drug products, vaccines, and adjuvants.

Detection of Endotoxin in Nano-formulations Using Limulus Amoebocyte Lysate LAL Assays

Detection of endotoxins in engineered nanomaterials represents one of the grand challenges in the field of nanomedicine. Here, we present a case study that describes the framework composed of three different LAL formats to estimate potential endotoxin contamination in nanoparticles.

When present in pharmaceutical products, a Gram-negative bacterial cell wall component endotoxin (often also called lipopolysaccharide) can cause ...

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The human Fibroblast Growth Factor Receptor (FGFR) family comprises four members, namely, FGFR1, FGFR2, FGFR3, and FGFR4, that are involved in various biological activities including cell proliferation, survival, migration and differentiation. Several aberrations in the FGFR signaling pathway, owing to mutations or gene amplification events, have been identified in various types of cancers. Hence, recent research has focused on developing strategies involving therapeutic targeting of FGFRs. Current FGFR inhibitors at various stages of pre-clinical and clinical development include either small molecule inhibitors of tyrosine kinases or monoclonal antibodies, with only a few peptide- based inhibitors in the pipeline. Here, we provide a protocol using phage display technology to screen small peptides as antagonists of FGFR2. Briefly, a library of phage-displayed peptides was incubated in a plate coated with FGFR2. Subsequently, unbound phage was washed off by TBST (TBS + 0.1% [v/v] Tween-20), and bound phage was eluted with 0.2 M glycine-HCl buffer (pH 2.2). The eluted phage was further amplified and used as input for the next round of biopanning. Following three rounds of biopanning, the peptide sequences of individual phage clones were identified by DNA sequencing. Finally, the screened peptides were synthesized and analyzed for affinity and biological activity.

Herein, we present a detailed protocol for screening small peptides that bind to FGFR2 using a phage display peptide library. We further analyze the affinity of the selected peptides toward FGFR2 in vitro and its ability to suppress cell proliferation.

The human Fibroblast Growth Factor Receptor (FGFR) family comprises four members, namely, FGFR1, FGFR2, FGFR3, and FGFR4, that are involved in various ...

Simultaneous Quantification of Selected Kynurenines Analyzed by Liquid Chromatography-Mass Spectrometry in Medium Collected from Cancer Cell Cultures

The kynurenine pathway and the tryptophan catabolites called kynurenines have received increased attention for their involvement in immune regulation and cancer biology. An in vitro cell culture assay is often used to learn about the contribution of different tryptophan catabolites in a disease mechanism and for testing therapeutic strategies. Cell culture medium that is rich in secreted metabolites and signaling molecules reflects the status of tryptophan metabolism and other cellular events. New protocols for the reliable quantification of multiple kynurenines in the complex cell culture medium are desired to allow for a reliable and quick analysis of multiple samples. This can be accomplished with liquid chromatography coupled with mass spectrometry. This powerful technique is employed in many clinical and research laboratories for the quantification of metabolites and can be used for measuring kynurenines.
Presented here is the use of liquid chromatography coupled with single quadrupole mass spectrometry (LC-SQ) for the simultaneous determination of four kynurenines, i.e., kynurenine, 3-hydroxykynurenine, 3-hydroxyanthranilic, and xanthurenic acid in the medium collected from in vitro cultured cancer cells. SQ detector is simple to use and less expensive compared to other mass spectrometers. In the SQ-MS analysis, multiple ions from the sample are generated and separated according to their specific mass-to-charge ratio (m/z), followed by the detection using a Single Ion Monitoring (SIM) mode.
This paper draws the attention on the advantages of the reported method and indicates some weak points. It is focused on critical elements of LC-SQ analysis including sample preparation along with chromatography and mass spectrometry analysis. The quality control, method calibration conditions and matrix effect issues are also discussed. We described a simple application of 3-nitrotyrosine as one analog standard for all target analytes. As confirmed by experiments with human ovary and breast cancer cells, the proposed LC-SQ method&#160;generates reliable results and can be further applied to other in vitro cellular models.

Described here is a protocol for the determination of four different tryptophan metabolites generated in the kynurenine pathway (kynurenine, 3-hydroxykynurenine, xanthurenic acid, 3-hydroxyanthranilic acid) in the medium collected from cancer cell cultures analyzed by liquid chromatography coupled with a single quadrupole mass spectrometry.

The kynurenine pathway and the tryptophan catabolites called kynurenines have received increased attention for their involvement in immune regulation and ...

The Quantification of Injectability by Mechanical Testing

Injectable biomaterials are becoming increasingly popular for the minimally invasive delivery of drugs and cells. These materials are typically more viscous than traditional aqueous injections and may be semi-solid, therefore, their injectability cannot be assumed. This protocol describes a method to objectively assess the injectability of these materials using a standard mechanical tester. The syringe plunger is compressed by the crosshead at a set rate, and the force is measured. The maximum or plateau force value can then be used for comparison between samples, or to an absolute force limit. This protocol can be used with any material, and any syringe and needle size or geometry. The results obtained may be used to make decisions about formulations, syringe and needle sizes early in the translational process. Further, the effects of altering formulations on injectability may be quantified, and the optimum time to inject temporally changing materials determined. This method is also suitable as a reproducible way to examine the effects of injection on a material, to study phenomena such as self-healing and filter pressing or study the effects of injection on cells. This protocol is faster and more directly applicable to injectability than rotational rheology, and requires minimal post processing to obtain key values for direct comparisons.

Presented here is a protocol for quantitatively evaluating the injectability of a material through a syringe-needle system using a standard mechanical testing rig.

Injectable biomaterials are becoming increasingly popular for the minimally invasive delivery of drugs and cells. These materials are typically more ...

Quantification of Mouse Heart Left Ventricular Function, Myocardial Strain, and Hemodynamic Forces by Cardiovascular Magnetic Resonance Imaging

Mouse models have contributed significantly to understanding genetic and physiological factors involved in healthy cardiac function, how perturbations result in pathology, and how myocardial diseases may be treated. Cardiovascular magnetic resonance imaging (CMR) has become an indispensable tool for a comprehensive in vivo assessment of cardiac anatomy and function. This protocol shows detailed measurements of mouse heart left ventricular function, myocardial strain, and hemodynamic forces using 7-Tesla CMR. First, animal preparation and positioning in the scanner are demonstrated. Survey scans are performed for planning imaging slices in various short- and long-axis views. A series of prospective ECG-triggered short-axis (SA) movies (or CINE images) are acquired covering the heart from apex to base, capturing end-systolic and end-diastolic phases. Subsequently, single-slice, retrospectively gated CINE images are acquired in a midventricular SA view, and in 2-, 3-, and 4-chamber views, to be reconstructed into high-temporal resolution CINE images using custom-built and open-source software. CINE images are subsequently analyzed using dedicated CMR image analysis software.
Delineating endomyocardial and epicardial borders in SA end-systolic and end-diastolic CINE images allows for the calculation of end-systolic and end-diastolic volumes, ejection fraction, and cardiac output. The midventricular SA CINE images are delineated for all cardiac time frames to extract a detailed volume-time curve. Its time derivative allows for the calculation of the diastolic function as the ratio of the early filling and atrial contraction waves. Finally, left ventricular endocardial walls in the 2-, 3-, and 4-chamber views are delineated using feature-tracking, from which longitudinal myocardial strain parameters and left ventricular hemodynamic forces are calculated. In conclusion, this protocol provides detailed in vivo quantification of the mouse cardiac parameters, which can be used to study temporal alterations in cardiac function in various mouse models of heart disease.

This study describes a comprehensive cardiovascular magnetic resonance imaging (CMR) protocol to quantify the left ventricular functional parameters of the mouse heart. The protocol describes the acquisition, post-processing, and analysis of the CMR images as well as assessment of different cardiac functional parameters.

Mouse models have contributed significantly to understanding genetic and physiological factors involved in healthy cardiac function, how perturbations ...

Affordable Oxygen Microscopy-Assisted Biofabrication of Multicellular Spheroids

Multicellular spheroids are important tools for studying tissue and cancer physiology in 3D and are frequently used in tissue engineering as tissue assembling units for biofabrication. While the main power of the spheroid model is in mimicking physical-chemical gradients at the tissue microscale, the real physiological environment (including dynamics of metabolic activity, oxygenation, cell death, and proliferation) inside the spheroids is generally ignored. At the same time, the effects of the growth medium composition and the formation method on the resulting spheroid phenotype are well documented. Thus, characterization and standardization of spheroid phenotype are required to ensure the reproducibility and transparency of the research results. The analysis of average spheroid oxygenation and the value of O2 gradients in three dimensions (3D) can be a simple and universal way for spheroid phenotype characterization, pointing at their metabolic activity, overall viability, and potential to recapitulate in vivo tissue microenvironment. The visualization of 3D oxygenation can be easily combined with multiparametric analysis of additional physiological parameters (such as cell death, proliferation, and cell composition) and applied for continuous oxygenation monitoring and/or end-point measurements. The loading of the O2 probe is performed during the stage of spheroid formation and is compatible with various protocols of spheroid generation. The protocol includes a high-throughput method of spheroid generation with introduced red and near-infrared emitting ratiometric fluorescent O2 nanosensors and the description of multi-parameter assessment of spheroid oxygenation and cell death before and after bioprinting. The experimental examples show comparative O2 gradients analysis in homo- and hetero-cellular spheroids as well as spheroid-based bioprinted constructs. The protocol is compatible with a conventional fluorescence microscope having multiple fluorescence filters and a light-emitting diode as a light source.

The protocol describes high-throughput spheroid generation for bioprinting using the multi-parametric analysis of their oxygenation and cell death on a standard fluorescence microscope. This approach can be applied to control the spheroids viability and perform standardization, which is important in modeling 3D tissue, tumor microenvironment, and successful (micro)tissue biofabrication.

Multicellular spheroids are important tools for studying tissue and cancer physiology in 3D and are frequently used in tissue engineering as tissue ...

High-Speed Ultraviolet Photoacoustic Microscopy for Histological Imaging with Virtual-Staining assisted by Deep Learning

Surgical margin analysis (SMA), an essential procedure to confirm the complete excision of cancerous tissue in tumor resection surgery, requires intraoperative diagnostic tools to avoid repeated surgeries due to a positive surgical margin. Recently, by taking the advantage of the high intrinsic optical absorption of DNA/RNA at 266 nm wavelength, ultraviolet photoacoustic microscopy (UV-PAM) has been developed to provide high-resolution histological images without labeling, showing great promise as an intraoperative tool for SMA. To enable the development of UV-PAM for SMA, here, a high-speed and open-top UV-PAM system is presented, which can be operated similarly to conventional optical microscopies. The UV-PAM system provides a high lateral resolution of 1.2 &#181;m, and a high imaging speed of 55 kHz A-line rate with one-axis galvanometer mirror scanning. Moreover, to ensure UV-PAM images can be easily interpreted by pathologists without additional training, the original grayscale UV-PAM images are virtually stained by a deep-learning algorithm to mimic the standard hematoxylin- and eosin-stained images, enabling training-free histological analysis. Mouse brain slice imaging is performed to demonstrate the high performance of the open-top UV-PAM system, illustrating its great potential for SMA applications.

A high-speed and open-top ultraviolet photoacoustic microscope that can provide histological images intraoperatively for surgical margin analysis is demonstrated, including the system configuration, optical alignment, sample preparation, and experimental procedures.