Name: dissection, microct scanning and morphometric analyses of the baculum
Uploaded: 2017-03-19T15:00:00.000+00:00
Duration: 4 min 32 s
Description: Watch this Scientific Journal Video about Dissection, MicroCT Scanning and Morphometric Analyses of the Baculum at JoVE.com

Tim Daley and Andrew Smith provided many useful computational discussions during the early days; Tim Daley wrote the program rotate_translate_cylindrical necessary for Protocol 5. Computational resources were provided by the High Performance Computing Cluster at the University of Southern California. This work was supported by NIH grant #GM098536 (MDD).

All procedures and personnel were approved by the University of Southern California&#39;s Institute for Animal Care and Use Committee (IACUC), protocol #11394.
1. Baculum Dissection and Preparation
<ol>
	<li>Euthanize a sexually mature male mouse via carbon dioxide over-exposure, according to protocols set forth by the relevant Institutional Animal Care and Use Committee (IACUC).</li>
	<li>Lay the animal in the supine position, and protract the penis by applying pressure with thumbs lateral to the preputial opening.</li>
	<li>Once the penis is protracted, extend the tissue through the prepuce as far as possible.</li>
	<li>With scissors, cut the penile body proximal to the glans penis where the baculum resides.</li>
	<li>Transfer the dissected penis to a 1.7 mL tube and add 200 &#181;L tap water. Make certain that the penis is fully submerged in the liquid.</li>
	<li>Incubate the tissue in water at ~50 &#176;C for 3-5 days.</li>
	<li>After proper incubation, remove the surrounding tissue from the baculum, using forceps under a dissection microscope. Gently squirt 70% ethanol to push off remaining tissue and clean the bone.</li>
	<li>Place the dissected baculum into a new microcentrifuge tube with the cap open. Leave cap open O/N to dry out bone.</li>
</ol>
2. MicroCT Scanning
<ol>
	<li>Press a microCT scan cylindrical holder into a brick of florist foam to create a cylinder of florist foam.</li>
	<li>Extract the cylinder of florist foam and cut slices ~2-5 cm thick.</li>
	<li>Push dried bacula into the florist foam, around the periphery of an individual slice to minimize interference during scanning. The precise orientation of bones should be remarked allowing for proper identification of individual specimens in Protocol 4.</li>
	<li>Gently place the slice with the embedded bones into the microCT holder.</li>
	<li>Acquire microCT scans. In the case of mouse bacula14, we used a uCT50 scanner (Scanco Medical AG, Bruttisellen, Switzerland) at the USC Molecular Imaging Center under the following settings: 90 kVp, 155 &#181;A, 0.5 mm Al filter, 750 projections per 180 (360 coverage), exposure time of 500 ms, and voxel size of 15.5 mm.</li>
</ol>
3. MicroCT Processing: Converting a .DCM Stack to a Single .xyz File
NOTE: Each microCT scan produces a stack of .DCM, or &#34;dicom&#34;, files that represent image slices taken through the object. All downstream computational geometry requires flat .xyz files, which is simply a text file that contains four columns &#8211; the x, y, and z coordinates of each pixel, and the intensity of the pixel, ranging from -5,000 (black) to +5,000 (white). A pixel threshold above 3,000 generally works well as a threshold for defining bones.
<ol>
	<li>Install Python (www.python.org) and the PYTHON modules COMMANDS, DICOM, PYLAB, SYS, and NUMPY.</li>
	<li>Open &#34;01_process_dicom.py&#34;{Figshare} with any text editor. Under the Variables section, change path, pixel thresholds, and directory names as necessary.</li>
	<li>Run &#34;python 01_process_dicom.py&#34;. Progress will be printed to screen. Within each directory named in step 3.2, a new file is made named; for example, directory_name.PT3000.xyz, where PT3000 indicates the pixel threshold indicated in step 3.2.</li>
</ol>
4. MicroCT processing: Segmenting-out Individual Specimen .xyz Files
<ol>
	<li>Install R (https://www.r-project.org/) with the library RGL.</li>
	<li>Open the file &#39;02_segment_dicoms.r&#39;{Figshare} with any text editor. Under the Variables section, change the path name to point to the .xyz file created in Protocol 3 above.</li>
	<li>From within R, run the command &#34;source(&#39;02_segment_dicoms.r&#39;)&#34; (without the double quotes).</li>
	<li>After the three dimensional image of the .xyz file created in Protocol 3 appears, enter the number of specimens in the overall .xyz file. Then label and select the points from each specimen using the scroll and zoom functions. 
	NOTE: In the background, separate .xyz files will be made for each specimen. These appear in a directory named, for example, XYZ_FILES_PT3000, where PT3000 indicates the pixel threshold used.</li>
</ol>
5. &#34;Aligning&#34; Specimen .xyz Files to Common Coordinates.
<ol>
	<li>Open the Python script &#34;03_transform.py&#34;{Figshare}, which requires the additional module mattdean_modules.py{Figshare}, as well as two self-standing applications: &#34;rotate_translate_cylindrical&#34; (https://github.com/timydaley/dean_cylindrical_tranform) and &#8220;qconvex&#8221; (www.qhull.org/html/qconvex.htm) that are used by this script.</li>
	<li>Under the Variables section, identify the full path names to mattdean_modules.py, rotate_path and qconvex_dir. In addition, identify the full path to the directory containing the individual .xyz files created in step 4.</li>
	<li>Run 03_transform.py, which creates a new file per specimen with the suffix .TRANSFORMED.xyz.</li>
</ol>
6. &#34;Slicing&#34; Aligned Specimen .xyz Files to Identify Semi-landmarks.
<ol>
	<li>Open and run the Python script &#34;04_identify_landmarks.py&#34;{Figshare}. In the Variables section, identify full path names to the directory containing the .TRANSFORMED.xyz files. This script identifies 802 semi-landmarks that can be used to quantify size and shape of the structure.</li>
</ol>

<ol>
	<li>Slice, D. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Geometrics+morphometrics.">Geometrics morphometrics.</a> Annu. Rev. Anthropol. 36, 261-281 (2007).</li><li>Slice, D. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Modern morphometrics in physical anthropology. 6, (2005).</li><li>Zelditch, M. L., Swiderski, D. L., Sheets, H. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Geometric morphometrics for biologists: a primer. , (2012).</li><li>Bookstein, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Morphometric tools for landmark data: geometry and biology. , (1991).</li><li>Rohlf, F. J., Marcus, L. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Revolution+in+Morphometrics.">A Revolution in Morphometrics.</a> Trends. Ecol. Evol. 8 (4), 129-132 (1993).</li><li>Zelditch, M. L., Swiderski, D. L., Sheets, H. D., Fink, W. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Geometric morphometrics for biologists: a primer. , (2004).</li><li>Rohlf, F. J., Slice, D. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Extensions+of+the+Procrustes+method+for+the+optimal+superimposition+of+landmarks.">Extensions of the Procrustes method for the optimal superimposition of landmarks.</a> Syst. Zool. 39 (1), 40-59 (1990).</li><li>Gunz, P., Mitteroecker, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Semilandmarks:+a+method+for+quantifying+curves+and+surfaces.">Semilandmarks: a method for quantifying curves and surfaces.</a> Hystrix. 24 (1), 103-109 (2013).</li><li>Gunz, P., Ramsier, M., Kuhrig, M., Hublin, J. J., Spoor, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+mammalian+bony+labyrinth+reconsidered,+introducing+a+comprehensive+geometric+morphometric+approach.">The mammalian bony labyrinth reconsidered, introducing a comprehensive geometric morphometric approach.</a> J. Anat. 220 (6), 529-543 (2012).</li><li>Mitteroecker, P., Gunz, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advances+in+geometric+morphometrics.">Advances in geometric morphometrics.</a> Evol. Biol. 36 (2), 235-247 (2009).</li><li>Bookstein, F. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Landmark+methods+for+forms+without+landmarks:+morphometrics+of+group+differences+in+outline+shape.">Landmark methods for forms without landmarks: morphometrics of group differences in outline shape.</a> Med. Im. Anal. 1 (3), 225-243 (1997).</li><li>Gunz, P., Mitteroecker, P., Bookstein, F., Slice, D. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Modern morphometrics in physical anthropology. , 73-98 (2005).</li><li>Oxnard, C., O'Higgins, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biology+Clearly+Needs+Morphometrics.+Does+Morphometrics+Need+Biology?.">Biology Clearly Needs Morphometrics. Does Morphometrics Need Biology?.</a> Biological Theory. 4 (1), 84-97 (2009).</li><li>Schultz, N. G., 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=The+genetic+basis+of+baculum+size+and+shape+variation+in+mice.">The genetic basis of baculum size and shape variation in mice.</a> G3. 6 (5), 1141-1151 (2016).</li><li>Schultz, N. G., Lough-Stevens, M., Abreu, E., Orr, T. J., Dean, M. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+baculum+was+gained+and+lost+multiple+times+during+mammalian+evolution.">The baculum was gained and lost multiple times during mammalian evolution.</a> Integr Comp Biol. 56 (4), 644-656 (2016).</li><li>Dines, J. P., 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=Sexual+selection+targets+cetacean+pelvic+bones.">Sexual selection targets cetacean pelvic bones.</a> Evolution. 68 (11), 3296-3306 (2014).</li><li>Adams, D. C., Ot&#225;rola-Castillo, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=geomorph:+an+R+package+for+the+collection+and+analysis+of+geometric+morphometric+shape+data.">geomorph: an R package for the collection and analysis of geometric morphometric shape data.</a> Methods Ecol. Evol. 4 (4), 393-399 (2013).</li></ol>

The authors declare that they have no competing financial interests.

The critical steps in the above protocol are 1) dissecting the bacula, 2) gathering the microCT images, 3) converting the microCT output to a flat file of x-y-z coordinates, 4) segmenting out each specimen&#39;s point cloud, 5) transforming each specimen to a standardized coordinate system, and 6) defining semi-landmarks. These steps are easily modified to accommodate different objects.
These methods can likely be applied to any object that is essentially &#34;rod-shaped&#34;, or at least not too curved. Objects that curve back on themselves to become &#34;u-shaped&#34; cannot be currently analyzed, because slicing (Figure 1G) would return points from different parts of the object. Such objects could be accommodated in the future by computationally straightening the object prior to slicing.
We have presented a general method for mathematically defining semi-landmarks from shapes that lack solid landmarks. These general methods have been modified to study the evolution of whale pelvic and rib bones16, which have very different shapes. Our computational methods for defining landmarks should be applicable to any series of x-y-z coordinates. We employed microCT scanning here, given the small size of mouse bacula14. For larger bones, such as the whale pelvic and rib bones, we employed a laser scanner that reconstructed the surface of the bones16. It is important to visually inspect all sets of semi-landmarks to verify the quality of the method. The main advantage of our computational methods is that they precisely quantify the size and shape variation, and preserve the correspondence between distinct regions of the object.

The field of morphometrics includes a diversity of methods to quantify the size and shape of the biological form, a fundamental step in scientific inquiry1,2,3,4,5,6. Traditionally, the statistical analysis of size and shape begins by identifying landmarks on a biological structure, and then measuring linear distances, angles and ratios, which could be analyzed in a multivariate framework. Landmark-based Geometric Morphometrics is an approach that retains the spatial position of landmarks, preserving geometric information from data collection through analysis and visualization5. Generalized Procrustes Analysis (GPA) can be applied to remove variation in location, scale, and rotation of landmarks to produce an alignment between specimens that minimizes their squared differences - what remains is shape dissimilarity7.
An important concept of any morphometric analysis is homology, or the idea that one can reliably identify landmarks representing biologically meaningful and discrete features that correspond between specimens or structures. For example, human skulls have homologous processes, foramina, sutures, and ducts that can enable morphometric analyses. Unfortunately, the identification of corresponding landmarks is difficult across many biological structures, especially those with smooth surfaces or curves8,9,10.
We approach this problem below using computational geometry. The general workflow is to generate a three dimensional scan of the object that can be represented as a cloud of points, and then rotate and transform that point cloud so that all specimens are oriented on a common coordinate system. Then we mathematically define semi-landmarks from specific regions of the object. Discrete semi-landmarks placed on such regions are biologically arbitrary11. Conducting GPA and subsequent statistical analyses can produce undesirable artifacts8,12 because arbitrarily placed landmarks may not be biologically homologous. Therefore, we allow these semi-landmarks to mathematically &#34;slide&#34;. This procedure minimizes the potential difference between structures. As argued elsewhere the sliding algorithm used here is appropriate to quantify similar anatomical regions lacking easily identified corresponding landmarks3,6,8,10,11,12. These methods have their limitations13, but should be adaptable to objects of different size and shape.
Here, we illustrate how this method was applied in a recent study of the mouse baculum14, a bone in the penis that has been gained and lost multiple independent times during mammalian evolution15. We discuss the dissection and preparation of a specific bone, the baculum (Protocol 1), the generation of microCT images (Protocol 2), and the conversion of these images to a format that enables all downstream computational geometry (Protocols 3 and 4). After these steps, each specimen is represented by ~100K x-y-z coordinates. We then walk through a series of transformations that effectively align all specimens into a common orientation (Protocol 5), then define semi-landmarks from aligned specimens (Protocol 6). Protocols 1-4 should be similar regardless of the object being analyzed. Protocol 5 and Protocol 6 are specifically designed for a baculum, but it is our hope that by detailing these steps, investigators can imagine modifications that would be relevant for their object of interest. For example, modifications of these methods were applied to study whale pelvic bones and rib bones16.

<table><tbody><tr><td>Dissecting scissors</td><td>VWR</td><td>470106-338</td><td>Most sizes should work</td></tr><tr><td>Dissecting Forceps, Fine Tip, Curved</td><td>VWR</td><td>82027-406</td><td></td></tr><tr><td>1.7 mL microcentrifuge tube</td><td>VWR</td><td>87003-294</td><td></td></tr><tr><td>Absolute Ethanol</td><td>Fisher Scientific</td><td>CAS 64-17-5</td><td>To be diluted to 70% for dissections</td></tr><tr><td>Floral Foam</td><td>Wholesale Floral</td><td>6002-48-07</td><td></td></tr><tr><td>uCT50 scanner&amp;nbsp;</td><td>Scanco Medical AG, Bruttisellen, Switzerland</td><td></td><td></td></tr></tbody></table>

dissection, microct scanning and morphometric analyses of the baculum

Modern morphometrics provides powerful methods to quantify size and shape variation. A basic requirement is a list of coordinates that define landmarks; however such coordinates must represent homologous structures across specimens. While many biological objects consist of easily identified landmarks to satisfy the assumption of homology, many lack such structures. One potential solution is to mathematically place semi-landmarks on an object that represent the same morphological region across specimens. Here, we illustrate a recently developed pipeline to mathematically define semi-landmarks from the mouse baculum (penis bone). Our methods should be applicable to a wide range of objects.

The x-y-z coordinates of the semi-landmarks produced in Protocol 6 can be directly imported into any landmark-based geometric morphometrics analysis17. The computational pipeline above has been applied to study mouse bacula14, as well as whale pelvic and rib bones16. More details on the computational definition of semi-landmarks are presented here, in an attempt to help researchers visualize steps that might be modified to accommodate their particular object of interest. The baculum contains several unique features that were exploited to automate certain transformations. For example, after computationally cutting the bone into two halves along a proximal-distal axis, we identified the proximal half simply by comparing the total number of points (the proximal has more). As long as there exist unique features such as this, our methods should be adaptable to any object. In addition, it should be emphasized that we empirically determined certain thresholds, such as &#34;10% proximal&#34; that performed well in our baculum studies, but most certainly need to be reassessed for other objects.
Beginning in Protocol 5, the first computational step is to calculate the convex hull (the smallest set of points that contains all other points in a sample) to identify the two points that are furthest apart from each other. These two points (red spheres, Figure 1C) begin to define a new z-axis (red line, Figure 1C) that runs proximal-distal through the bone. In the case of the baculum, the half of the point cloud that contains more points is defined as the proximal end.
Second, the entire point cloud is transformed so that the proximal point takes on the x,y,z coordinates of 0,0,0 and the distal point takes on the x,y,z coordinates of 0,0,+z, where +z is some positive value dependent on the size of the bone. At the end of this step, a z-axis passes through the length of the bone. For procedures below, the length from the minimum to maximum z-coordinates will be referred to as Zlength.
Third, to correct for variance associated with the exact placement of the proximal and distal points identified above, the 10% most proximal and 10% most distal points are sampled separately (Figure 1D), their respective centroids identified (red spheres, Figure 1E) and the point cloud transformed such that the proximal centroid is 0,0,0, and the distal centroid is 0,0,+z, with a new z-axis that passes through the center of the specimen (red line, Figure 1E).
Fourth, the point cloud is rotated around the z-axis by first taking a slice of points in the proximal 15 to 15.25% Zlength of the structure (blue points, Figure 1E). This slice of points is flattened in the z dimension (i.e.&#160;z-coordinates are simply ignored), the convex hull taken, and the minimum bounding rectangle (the smallest rectangle that contains all other points) calculated. Imagine a line connecting the midpoints of the two short sides of this minimum bounding rectangle. We rotate the point cloud until these two midpoints become -x,0,+z and +x,0,+z, respectively, thus this line becomes a new x-axis. After transformation, the distance between the maximal and minimal x values are referred to as Xlength. A new file is created from specimen.xyz to specimen.TRANSFORMED.xyz.
Fifth, points within 1% Xlength of the z-axis are sliced out (blue points, Figure 1F), and the single most proximal and single most distal point identified from this central slice and labeled DISTAL and PROXIMAL, respectively. These are the first two semi-landmarks identified.
Sixth, 50 evenly spaced slices of points are sampled along the z-axis (red points, Figure 1G). Each slice is a thickness of 1% Zlength. Each slice is then flattened in the z dimension, and divided equally by 7 vertical lines (red lines, Figure 1H). Points within 2% Xlength of each line are kept (red points, Figure 1H), then the points with the maximum and minimum y-coordinate are kept, projected onto each respective line, and labeled VENTRAL and DORSAL, respectively. In addition, labels contain the slice number and the line number, for example P15_VENTRAL4 is the ventral point sampled from the 4th vertical line of the 15th slice. Importantly, every point labeled, for example, P15_VENTRAL4, occurs once and only once across all specimens, preserving correspondence. In addition to the ventral and dorsal points of each of the 7 lines (14 semi-landmarks total), the points with the maximum and minimum x-value are sampled and labeled LEFT and RIGHT, respectively. The y and z coordinates of LEFT and RIGHT are smoothed using the lowess function in R. For the baculum, a total of 16 semi-landmarks are defined per slice (red spheres, Figure 1H); with 50 slices plus the PROXIMAL and DISTAL semi-landmarks defined above, 802 semi-landmarks are sampled per specimen (green spheres, Figure 1I). All other points from the original microCT scan are discarded.
It should be noted that although ventral/dorsal and proximal/distal polarity was determined mathematically, all specimen alignments were visually confirmed and manually adjusted as required. In our sample of 369 bacula, approximately 10 had to be manually adjusted.
<img alt="Figure 1" src="/files/ftp_upload/55342/55342fig1.jpg" /> 
Figure 1: Visual Representation of the Computational Workflow (Protocol 4-6). (A) A screenshot from the 02_segment_dicoms.r script (Protocol 4), showing the assignment of distinct point clouds to individual specimens. (B) Enlarged view of one baculum, represented by a cloud of ~100K x-y-z points. (C) Identification of the two points furthest apart from each other (red spheres), used to define a new z-axis that runs proximal-distal through the bone (red line). (D) Sampling the proximal-most 10% and distal-most 10% of points (red points) provides a means to adjust for slight variance in the exact placement of the z-axis. (E) The centroids of the proximal-most 10% and distal-most 10% (red spheres) are used to define a new z-axis (red line). Then, a slice of points falling between 15.00-15.25% of this new z-axis (blue points) is taken to calculate the minimum bounding rectangle. The point cloud is rotated until the long side of the minimum bounding rectangle is parallel to a new x-axis. F) a slice of points running along the midline (blue points) is sampled and the proximal-most and distal-most point defined as a semi-landmark. G) 50 evenly spaced slices of points are sampled (red points), with H) showing one such slice. 16 points (red circles) are defined to capture the outline of each slice. I) When repeated across all slices, a total of 802 semi-landmarks (green spheres) define the structure and are used in all downstream morphometric applications. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55342/55342fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Dissection, MicroCT Scanning and Morphometric Analyses of the Baculum at JoVE.com

Dissection, MicroCT Scanning and Morphometric Analyses of the Baculum

Many biological structures lack easily definable landmarks, making it difficult to apply modern morphometric methods. Here we illustrate methods to study the mouse baculum (a bone in the penis), including dissection and microCT scanning, followed by computational methods to define semi-landmarks that are used to quantify size and shape variation.

Modern morphometrics provides powerful methods to quantify size and shape variation. A basic requirement is a list of coordinates that define landmarks; ...

dissection-microct-scanning-and-morphometric-analyses-of-the-baculum

Nanyang Technological University

Research

JoVE Journal

Bioengineering

7.5K Views.  University of Southern California (USC).  Vele biologische structuren ontbreken gemakkelijk definieerbare bezienswaardigheden, waardoor het moeilijk is om de moderne morfometrische methoden toe te passen. Hier tonen we methoden om de muis baculum (een bot in de penis), waaronder dissectie en microCT scannen, gevolgd door computationele werkwijzen semi-monumenten die worden gebruikt om de grootte en vorm kwantificeren variatie definiëren bestuderen. 

Video: Dissection, MicroCT Scanning and Morphometric Analyses of the Baculum

Measuring Bone Remodeling and Recreating the Tumor-Bone Microenvironment Using Calvaria Co-culture and Histomorphometry

Bone is a connective tissue constituted of osteoblasts, osteocytes, and osteoclasts and a mineralized extracellular matrix, which gives it its strength and flexibility and allows it to fulfill its functions. Bone is continuously exposed to a variety of stimuli, which in pathological conditions can deregulate bone remodeling. To study bone biology and diseases and evaluate potential therapeutic agents, it has been necessary to develop in vitro and in vivo models.
This manuscript describes the dissection process and culture conditions of calvarias isolated from neonatal mice to study bone formation and the bone tumor microenvironment. In contrast to in vitro and in vivo models, this ex vivo model allows preservation of the three-dimensional environment of the tissue as well as the cellular diversity of the bone while culturing under defined conditions to simulate the desired microenvironment. Therefore, it is possible to investigate bone remodeling and its mechanisms, as well as the interactions with other cell types, such as the interactions between cancer cells and bone.
The assays reported here use calvarias from 5-7 day old BALB/C mice. The hemi-calvarias obtained are cultured in the presence of insulin, breast cancer cells (MDA-MB-231), or conditioned medium from breast cancer cell cultures. After analysis, it was established that insulin induced new bone formation, while cancer cells and their conditioned medium induced bone resorption. The calvarial model has been successfully used in basic and applied research to study bone development and cancer-induced bone diseases. Overall, it is an excellent option for an easy, informative, and low-cost assay.

The ex vivo culture of bone explants can be a valuable tool for the study of bone physiology and the potential evaluation of drugs in bone remodeling and bone diseases. The presented protocol describes the preparation and culture of calvarias isolated from newborn mice skulls, as well as its applications.

Bone is a connective tissue constituted of osteoblasts, osteocytes, and osteoclasts and a mineralized extracellular matrix, which gives it its strength ...

Cancer Research

Establishment of a Segmental Femoral Critical-size Defect Model in Mice Stabilized by Plate Osteosynthesis

The use of tissue-engineered bone constructs is an appealing strategy to overcome drawbacks of autografts for the treatment of massive bone defects. As a model organism, the mouse has already been widely used in bone-related research. Large diaphyseal bone defect models in mice, however, are sparse and often use bone fixation which fills the bone marrow cavity and does not provide optimal mechanical stability. The objectives of the current study were to develop a critical-size, segmental, femoral defect in nude mice. A 3.5-mm mid-diaphyseal femoral ostectomy (approximately 25% of the femur length) was performed using a dedicated jig, and was stabilized with an anterior located locking plate and 4 locking screws. The bone defect was subsequently either left empty or filled with a bone substitute (syngenic bone graft or coralline scaffold). Bone healing was monitored noninvasively using radiography and in vivo micro-computed-tomography and was subsequently assessed by ex vivo micro-computed-tomography and undecalcified histology after animal sacrifice, 10 weeks postoperatively. The recovery of all mice was excellent, a full-weight-bearing was observed within one day following the surgical procedure. Furthermore, stable bone fixation and consistent fixation of the implanted materials were achieved in all animals tested throughout the study. When the bone defects were left empty, non-union was consistently obtained. In contrast, when the bone defects were filled with syngenic bone grafts, bone union was always observed. When the bone defects were filled with coralline scaffolds, newly-formed bone was observed in the interface between bone resection edges and the scaffold, as well as within a short distance within the scaffold. 
The present model describes a reproducible critical-size femoral defect stabilized by plate osteosynthesis with low morbidity in mice. The new load-bearing segmental bone defect model could be useful for studying the underlying mechanisms in bone regeneration pertinent to orthopaedic applications.

Although mouse models are invaluable tools for bone tissue engineering, models of long bone defects are sparse. This need motivated development of the present protocol which uses a locking plate with four screws and a dedicated jig to perform and stabilize a reproducible, femoral, critical-size defect with low morbidity.

The use of tissue-engineered bone constructs is an appealing strategy to overcome drawbacks of autografts for the treatment of massive bone defects. As a ...

Medicine

Rigid Embedding of Fixed and Stained, Whole, Millimeter-Scale Specimens for Section-free 3D Histology by Micro-Computed Tomography

For over a hundred years, the histological study of tissues has been the gold standard for medical diagnosis because histology allows all cell types in every tissue to be identified and characterized. Our laboratory is actively working to make technological advances in X-ray micro-computed tomography (micro-CT) that will bring the diagnostic power of histology to the study of full tissue volumes at cellular resolution (i.e., an X-ray Histo-tomography modality). Toward this end, we have made targeted improvements to the sample preparation pipeline. One key optimization, and the focus of the present work, is a straightforward method for rigid embedding of fixed and stained millimeter-scale samples. Many of the published methods for sample immobilization and correlative micro-CT imaging rely on placing the samples in paraffin wax, agarose, or liquids such as alcohol. Our approach extends this work with custom procedures and the design of a 3-dimensional printable apparatus to embed the samples in an acrylic resin directly into polyimide tubing, which is relatively transparent to X-rays. Herein, sample preparation procedures are described for the samples from 0.5 to 10 mm in diameter, which would be suitable for whole zebrafish larvae and juveniles, or other animals and tissue samples of similar dimensions. As proof of concept, we have embedded the specimens from Danio, Drosophila, Daphnia, and a mouse embryo; representative images from 3-dimensional scans for three of these samples are shown. Importantly, our methodology leads to multiple benefits including rigid immobilization, long-term preservation of laboriously-created resources, and the ability to re-interrogate samples.

We developed protocols and designed a custom apparatus to enable embedding of millimeter-scale specimens. We present sample preparation procedures with an emphasis on embedding in acrylic resin and polyimide tubing to achieve rigid immobilization and long-term storage of specimens for the interrogation of tissue architecture and cell morphology by micro-CT.

For over a hundred years, the histological study of tissues has been the gold standard for medical diagnosis because histology allows all cell types in ...

Biomechanical Testing of Murine Tendons

Tendon disorders are common, affect people of all ages, and are often debilitating. Standard treatments, such as anti-inflammatory drugs, rehabilitation, and surgical repair, often fail. In order to define tendon function and demonstrate efficacy of new treatments, the mechanical properties of tendons from animal models must be accurately determined. Murine animal models are now widely used to study tendon disorders and evaluate novel treatments for tendinopathies; however, determining the mechanical properties of mouse tendons has been challenging. In this study, a new system was developed for tendon mechanical testing that includes 3D-printed fixtures that exactly match the anatomies of the humerus and calcaneus to mechanically test supraspinatus tendons and Achilles tendons, respectively. These fixtures were developed using 3D reconstructions of native bone anatomy, solid modeling, and additive manufacturing. The new approach eliminated artifactual gripping failures (e.g., failure at the growth plate failure rather than in the tendon), decreased overall testing time, and increased reproducibility. Furthermore, this new method is readily adaptable for testing other murine tendons and tendons from other animals.

The protocol describes efficient and reproducible tensile biomechanical testing methods for murine tendons through the use of custom-fit 3D printed fixtures.

Tendon disorders are common, affect people of all ages, and are often debilitating. Standard treatments, such as anti-inflammatory drugs, rehabilitation, ...

Analysis of Craniomaxillofacial Malformations in Mice Using Three-dimensional Microcomputed Tomography

To model craniofacial malformations caused by vitamin A deficiency (VAD), we expressed a dominant-negative retinoid receptor mutation in osteoblasts to specifically inhibit RAR transcriptional activity in mice. This approach allowed us to investigate the effects of VAD on cranial hypomineralization, mandibular deformity, and clavicular hypoplasia in clinical cases. In this study, microcomputed tomography (microCT) scanning of the craniomaxillofacial region of mice represented a valuable tool for studying the growth and development of this animal model. The manual estimation of images is both time-consuming and inaccurate. Hence, here, we present a straightforward, efficient, and accurate approach for segmenting and quantifying the microCT images of each craniomaxillofacial bone. MicroCT software was used to slice the mandible, frontal bone, parietal bone, nasal bone, premaxilla, maxilla, interparietal bone, and occipital bone of mice and measure their corresponding lengths and widths. This segmentation method can be applied to study growth and development in developmental biology, biomedicine, and other related sciences and allows researchers to analyze the effects of genetic mutations on individual craniofacial bones.

Here, we describe in depth a method, which is based on microcomputed tomography, to segment and measure 3D models of craniomaxillofacial bones in mice, for better assessment of craniomaxillofacial bone development in mice than what is possible with current methods.

To model craniofacial malformations caused by vitamin A deficiency (VAD), we expressed a dominant-negative retinoid receptor mutation in osteoblasts to ...

Developmental Biology

Principles and Protocols of Mechanical Testing for Bone Fracture Susceptibility

Practical Considerations for the Design, Execution, and Interpretation of Studies Involving Whole-Bone Bending Tests of Rodent Bones

Skeletal fragility leading to fracture is an American public health crisis resulting in 1.5 million fractures each year and $18 billion in direct care costs. The ability to understand the mechanisms underlying bone disease and the response to treatment is not only desired, but critical. Mechanical testing of bone serves as a valuable technique for understanding and quantifying a bone&#39;s susceptibility to fracture. While this method appears simple to perform, inappropriate and inaccurate conclusions may be reached if governing assumptions and key steps are disregarded by the user. This has been observed across disciplines as studies continue to be published with misuse of methods and incorrect interpretation of results. This protocol will serve as a primer for the principles associated with mechanical testing along with the application of these techniques-from considerations of sample size through tissue harvesting and storage, to data analysis and interpretation. With this in hand, valuable information regarding a bone&#39;s susceptibility to fracture may be obtained, furthering understanding for both academic research and clinical solutions.

Author Spotlight: Enhancing Accuracy and Reproducibility in Whole Bone Bending Tests 

Mechanical testing of rodent bones is a valuable method for extracting information regarding a bone's susceptibility to fracture. Lacking proper practical understanding, the results may be overinterpreted or lack validity. This protocol will serve as a guide to ensure mechanical tests are performed accurately to provide valid and functional data.

Skeletal fragility leading to fracture is an American public health crisis resulting in 1.5 million fractures each year and $18 billion in direct care ...

A Morphometric and Cellular Analysis Method for the Murine Mandibular Condyle

The temporomandibular joint (TMJ) has the capacity to adapt to external stimuli, and loading changes can affect the position of condyles, as well as the structural and cellular components of the mandibular condylar cartilage (MCC). This manuscript describes methods for analyzing these changes and a method for altering the loading of the TMJ in mice (i.e., compressive static TMJ loading). The structural evaluation illustrated here is a simple morphometric approach that uses the Digimizer software and is performed in radiographs of small bones. In addition, the analysis of cellular changes leading to alterations in collagen expression, bone remodeling, cell division, and proteoglycan distribution in the MCC is described. The quantification of these changes in histological sections - by counting the positive fluorescent pixels using image software and measuring the distance mapping and stained area with Digimizer - is also demonstrated. The methods shown here are not limited to the murine TMJ, but could be used on additional bones of small experimental animals and in other regions of endochondral ossification.

This manuscript presents methods for analyzing morphometric and cellular changes within the mandibular condyle of rodents.

The temporomandibular joint (TMJ) has the capacity to adapt to external stimuli, and loading changes can affect the position of condyles, as well as the ...

Biology

HE Staining and Micro-CT to Evaluate Murine Trabecular Bone Microarchitecture

Trabecular Bone Microarchitecture Evaluation in an Osteoporosis Mouse Model

Bone microstructure refers to the arrangement and quality of bone tissue at the microscopic level. Understanding the bone microstructure of the skeleton is crucial for gaining insight into the pathophysiology of osteoporosis and improving its treatment. However, handling bone samples can be complex due to their hard and dense properties. Secondly, specialized software makes image processing and analysis difficult. In this protocol, we present a cost-effective and easy-to-use solution for trabecular bone microstructure analysis. Detailed steps and precautions are provided. Micro-CT is a non-destructive three-dimensional (3D) imaging technique that provides high-resolution images of trabecular bone structure. It allows for the objective and quantitative evaluation of bone quality, which is why it is widely regarded as the gold standard method for bone quality assessment. However, histomorphometry remains indispensable as it offers crucial cellular-level parameters, bridging the gap between two-dimensional (2D) and 3D assessments of bone specimens. As for the histologic techniques, we chose to decalcify the bone tissue and then perform traditional paraffin embedding. In summary, combining these two methods can provide more comprehensive and accurate information on bone microstructure.

Author Spotlight: An Economic and Efficient Method for Quantitative Evaluation of Bone Microarchitecture in a Murine Osteoporosis Model 

This protocol presents an economical and efficient method for quantitative evaluation of bone microarchitecture in a mouse model of osteoporosis by combining Hematoxylin-Eosin (HE) staining and micro-computed tomography (Micro-CT) techniques.

Bone microstructure refers to the arrangement and quality of bone tissue at the microscopic level. Understanding the bone microstructure of the skeleton ...

Skeletal Phenotype Analysis of a Conditional Stat3 Deletion Mouse Model

Transgenic mouse models are powerful for understanding the critical genes controlling osteoclast differentiation and activity, and for studying mechanisms and pharmaceutical treatments of osteoporosis. Cathepsin K (Ctsk)-Cre mice have been widely used for functional studies of osteoclasts. The signal transducer and activator of transcription 3 (STAT3) is relevant in bone homeostasis, but its role in osteoclasts in vivo remains poorly defined. To provide the in vivo evidence that STAT3 participates in osteoclast differentiation and bone metabolism, we generated an osteoclast-specific Stat3 deletion mouse model (Stat3 fl/fl; Ctsk-Cre) and analyzed its skeletal phenotype. Micro-CT scanning and 3D reconstruction implied increased bone mass in the conditional knockout mice. H&#38;E staining, calcein and alizarin red double staining, and tartrate-resistant acid phosphatase (TRAP) staining were performed to detect bone metabolism. In short, this protocol describes some canonical methods and techniques to analyze skeletal phenotype and to study the critical genes controlling osteoclast activity in vivo.

Skeletal Phenotype Analysis of a Conditional Stat3 Deletion Mouse Model

This protocol describes a canonical method to understand the critical genes controlling osteoclast activity in vivo. This method uses a transgenic mouse model and some canonical techniques to analyze skeletal phenotype.

Transgenic mouse models are powerful for understanding the critical genes controlling osteoclast differentiation and activity, and for studying mechanisms ...

Induction and Diverse Assessment Indicators of Experimental Autoimmune Encephalomyelitis

Multiple sclerosis (MS) is a typical autoimmune disease of the central nervous system (CNS) characterized by inflammatory infiltration, demyelination, and axonal damage. Currently, there are no measures to cure MS completely, but multiple disease-modifying therapies (DMT) are available to control and mitigate disease progression. There are significant similarities between the CNS pathological features of experimental autoimmune encephalomyelitis (EAE) and MS patients. EAE has been widely used as a representative model to determine MS drugs' efficacy and explore the development of new therapies for MS disease. Active induction of EAE in mice has a stable and reproducible effect and is particularly suitable for studying the effects of drugs or genes on autoimmune neuroinflammation. The method of immunizing C57BL/6J mice with myelin oligodendrocyte glycoprotein (MOG35-55) and the daily assessment of disease symptoms using a clinical scoring system is mainly shared. Given the complex etiology of MS with diverse clinical manifestations, the existing clinical scoring system can't satisfy the assessment of disease treatment. To avoid the shortcomings of a single intervention, new indicators to assess EAE based on clinical manifestations of anxiety-like moods and osteoporosis in MS patients are created to provide a more comprehensive assessment of MS treatment.

The present protocol describes the induction of experimental autoimmune encephalomyelitis in a mouse model using myelin oligodendrocyte glycoprotein and monitoring the disease process using a clinical scoring system. Experimental autoimmune encephalomyelitis-related symptoms are analyzed using mouse femur micro-computed tomography analysis and open field test to assess the disease process comprehensively.

Multiple sclerosis (MS) is a typical autoimmune disease of the central nervous system (CNS) characterized by inflammatory infiltration, demyelination, and ...

Dissection, MicroCT Scanning and Morphometric Analyses of the Baculum

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