The authors would like to thank the Biomarker Imaging&#160;Research Laboratory (BIRL) at Sunnybrook Research Institute for their histology services. Support for this work was provided by the Terry Fox Foundation, the Canadian Breast Cancer Foundation&#8208;the Prairie&#8208;NWT as well as a CIHR grant, #MOP-97996.

1. Specimen
<ol>
	<li>Excise the mammary glands surgically from wild-type CDH1 as well as Igfbp7-null mice three days post onset of lactation.</li>
	<li>Spread the glands onto glass slides to help regain native mammary gland morphology.</li>
</ol>
2. Fixation and Tissue Processing
<ol>
	<li>Fix the mammary glands in neutral buffered 4% PFA O/N at 4&#160;oC.</li>
	<li>Store the glands in 70% ethanol prior to tissue processing.</li>
	<li>Transfer the glands to small tissue processing cassettes.</li>
	<li>Process the tissues using an automated tissue processor
	<ol>
		<li>Dehydrate the tissues in increasing ethanol and xylene baths of 70% ethanol for 45 min, 2 times in 95% ethanol for 45 min, 3 times in 100% ethanol for 1 hr and 2 times in xylene for 45 min.</li>
		<li>Permeate the tissues with paraffin 3 times for 1 hr each in a vacuum with applied pressure.</li>
	</ol>
	</li>
	<li>Embed the tissues in paraffin to form blocks, for sectioning.</li>
</ol>
3. Histology and Blockface Imaging
<ol>
	<li>Trim the paraffin blocks using a rotary microtome until the excess paraffin is removed.</li>
	<li>Use a vertical milling machine to drill 1 mm holes in at least two corners of the paraffin block perpendicular to the cassette.</li>
	<li>Mount the tissue block on the rotary microtome.</li>
	<li>Set up the blockface imaging system19 in front of the microtome.</li>
	<li>Capture optical blockface image prior to sectioning.</li>
	<li>Cut ribbons of four sections at 5 &#956;m thickness on the microtome.
	<ol>
		<li>Transfer the ribbons to the cold water bath.</li>
		<li>Separate the second and fourth sections of the ribbon and mount them on microscope slides. Choosing the second and fourth sections provides a 5 &#181;m gap between sections.</li>
		<li>Expand each section in a warm water bath (48 oC) to unwrinkle it, then re-mount it on the microscope slide. 
		NOTE: Cutting, mounting, unwrinkling the sections cause some distortions on the section, such as tear, fold, shrinkage, and expansion. These artifacts complicate the registration of the histology sections.</li>
		<li>Stain the sections with H&#38;E using an automatic stainer.</li>
		<li>Coverslip the slides using an automatic coverslipper.</li>
		<li>Digitize the slides using a digital histology slide scanner at the resolution of interest. For this protocol the magnification is 20x and the resolution is 0.47 &#956;m.</li>
		<li>Down-sample the histology images to the resolution of blockface images, 18 &#956;m.</li>
	</ol>
	</li>
</ol>
4. Image Registration
<ol>
	<li>Image Segmentation and point Selection
	<ol>
		<li>In blockface images measure the pixel values of the registration holes and use the average value as a fixed threshold to segment the registration holes in the corners of the paraffin block.</li>
		<li>Since some additional parts might also be segmented by using the fixed threshold, use the circularity and the area of the segmented objects to find the holes and discard the extra objects. To do this, write a small code and find the ratio of (4&#960; x area)/(perimeter)2 for the segmented objects. This ratio for round objects is 1.</li>
		<li>For each mammary gland, select one blockface image as reference and align the rest of the blockface images to the reference by using the centre of the registration holes and landmark-based registration techniques.</li>
		<li>For the aligned blockface images, manually segment or extract the tissue from the background. Use the most sizable object in the mask for the rest of the protocol.</li>
		<li>For H&#38;E sections follow the steps below for automatic segmentation.
		<ol>
			<li>Use Otsu thresholding technique20 to segment images from the background and create binary masks of the histology images.</li>
			<li>Identify and select the most sizable object in each mask using the histogram of the labeled objects.</li>
			<li>Extract the one pixel wide boundary points from both histology and blockface masks.</li>
			<li>Use Chain code algorithm21, to represent the boundary points by a sequence of piecewise linear fits.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Initial Rigid Registration
	<ol>
		<li>Use Fourier Descriptors algorithm22, to find the initial rigid transform between the boundary points of histology and their corresponding blockface images. This initial transform includes the translation, rotation and scale factors.</li>
		<li>Transform each histology image with the initial transform obtained from the previous step.</li>
	</ol>
	</li>
	<li>Refinement of the Rigid Registration
	<ol>
		<li>Remove the high curvature edge sections from the histology contour using a rolling ball filter23.</li>
		<li>Select 500 points from the remaining histology boundary points randomly using uniform distribution.</li>
		<li>Transform the the histology random boundary points with the initial transformation obtained from Fourier descriptors.</li>
		<li>Select the whole set of blockface boundary points and use Iterative Closest Points (ICP) algorithm24 to find the rigid transformation between the blockface boundary points, destination, and histology random boundary points.</li>
		<li>Transform the aligned histology images obtained from the previous step and the stack of aligned histology images creates the histology volume.</li>
		<li>Use a 3D visualization software to create a visual image of the histology volume.</li>
	</ol>
	</li>
	<li>Viewing the Stack of Images at 5x magnification
	<ol>
		<li>Down-sample the original histology images to 5x magnification.</li>
		<li>Crop the region of interest in one of the histology images.</li>
		<li>Calculate the location of that region in other 5x histology images using the combination of the rigid transformations from the two steps of registration.</li>
		<li>Crop the regions of interest to the same size region in all other histology images.</li>
		<li>Finally refine the alignment between the regions manually. Write a program that overlays two images and allows for selecting the values for rotation and translation of one of the images over the other one and then saves the transformed image when the alignment is accepted.</li>
		<li>View the stacks of the aligned 5x histology regions using a 3D visualization software.</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Sunkin, S. 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=Brain+Atlas:+An+integrated+spatiotemporal+port+for+exploring+the+central+nervous+system.">Brain Atlas: An integrated spatiotemporal port for exploring the central nervous system.</a> Nucleic Acids Research. 41, 996-1008 (2012).</li><li>Shen, E. H., Overly, C. C., Jones, A. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Allen+Human+Brain+Atlas:+Comprehensive+gene+expression+mapping+of+the+human+brain.">The Allen Human Brain Atlas: Comprehensive gene expression mapping of the human brain.</a> Trends in Neurosciences. 35 (12), 711-714 (2012).</li><li>Trifunovi&#263;, D., Karali, M., Camposampiero, D., Ponzin, D., Banfi, S., Marigo, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+high-resolution+RNA+expression+atlas+of+retinitis+pigmentosa+genes+in+human+and+mouse+retinas.">A high-resolution RNA expression atlas of retinitis pigmentosa genes in human and mouse retinas.</a> Invest. Ophthalmol. Vis. Sci. 49 (6), 2330-2336 (2008).</li><li>Evdokimova, V., 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=IGFBP7+binds+to+the+IGF-1+receptor+and+blocks+its+activation+by+insulin-like+growth+factors.">IGFBP7 binds to the IGF-1 receptor and blocks its activation by insulin-like growth factors.</a> Science Signaling. 5 (255), 92 (2012).</li><li>Burger, A., Leyland-Jones, B., Banerjee, K., Spyropoulos, D., Seth, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Essential+roles+for+IGFBP-3+and+IGFBP-rP1+in+breast+cancer.">Essential roles for IGFBP-3 and IGFBP-rP1 in breast cancer.</a> European J. Cancer. 41 (11), 1515-1527 (2005).</li><li>Amemiya, Y., 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=Insulin+like+growth+factor+binding+protein-7+reduces+growth+of+human+breast+cancer+cells+and+xenografted+tumors.">Insulin like growth factor binding protein-7 reduces growth of human breast cancer cells and xenografted tumors.</a> Breast Cancer Res Treat. 126 (2), 373-384 (2011).</li><li>Benatar, T., 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=IGFBP7+reduces+breast+tumor+growth+by+induction+of+senescence+and+apoptosis+pathways.">IGFBP7 reduces breast tumor growth by induction of senescence and apoptosis pathways.</a> Breast Cancer Res Treat. 133 (2), 563-573 (2012).</li><li>Bardinet, E., 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=Co-registration+of+histological,+optical+and+MR+data+of+the+human+brain.">Co-registration of histological, optical and MR data of the human brain.</a> Medical Image Computing and Computer-Assisted Intervention-Part I. , 548-555 (2002).</li><li>Jacobs, M. A., Windham, J. P., Soltanian-Zadeh, H., Peck, D. J., Knight, R. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Registration+and+warping+of+magnetic+resonance+images+to+histological+sections.">Registration and warping of magnetic resonance images to histological sections.</a> Medical Physics. 26 (8), 1568-1578 (1999).</li><li>Zhan, Y., Ou, Y., Feldman, M., Tomaszeweski, J., Davatzikos, C., Shen, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Registering+histologic+and+MR+images+of+prostate+for+image-based+cancer+detection.">Registering histologic and MR images of prostate for image-based cancer detection.</a> Academic radiology. 14 (11), 1367-1381 (2007).</li><li>Dauguet, J., 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=Three-dimensional+reconstruction+of+stained+histological+slices+and+3D+non-linear+registration+with+in+vivo+MRI+for+whole+baboon+brain.">Three-dimensional reconstruction of stained histological slices and 3D non-linear registration with in vivo MRI for whole baboon brain.</a> Journal of Neuroscience Methods. 164 (1), 191-204 (2007).</li><li>Lazebnik, R. S., Lancaster, T. L., Breen, M. S., Lewin, J. S., Wilson, D. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Volume+registration+using+needle+paths+and+point+landmarks+for+evaluation+of+interventional+MRI+treatments.">Volume registration using needle paths and point landmarks for evaluation of interventional MRI treatments.</a> IEEE Transactions on Medical Imaging. 22 (5), 653-660 (2003).</li><li>Breen, M. S., Lazebnik, R. S., Wilson, D. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Three-dimensional+registration+of+magnetic+resonance+image+data+to+histological+sections+with+model-based+evaluation.">Three-dimensional registration of magnetic resonance image data to histological sections with model-based evaluation.</a> Annals of Biomedical Engineering. 33 (8), 1100-1112 (2005).</li><li>Mori, H., Borowsky, A. D., Bhat, R., Ghajar, C. M., Seiki, M., Bissell, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> The American Journal of Pathology. 180 (6), 2249-2256 (2012).</li><li>Gibb, M., Gilbert, D., Heiner, 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=Resolving+the+three-dimensional+histology+of+the+heart.">Resolving the three-dimensional histology of the heart.</a> Computational Methods in Systems Biology. , 2-16 (2012).</li><li>Wu, 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=Three-dimensional+virtual+microscopy+of+colorectal+biopsies.">Three-dimensional virtual microscopy of colorectal biopsies.</a> Archives of Pathology &amp; Laboratory Medicine. 129 (4), 507-510 (2005).</li><li>Arganda-Carreras, I., 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+Reconstruction+of+histological+sections:+Application+to+mammary+gland+tissue.">3D Reconstruction of histological sections: Application to mammary gland tissue.</a> Microscopy Research and Technique. 73 (11), 1019-1029 (2010).</li><li>Song, Y., Treanor, D., Bulpitt, A. J., Magee, D. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=3D+reconstruction+of+multiple+stained+histology+images.">3D reconstruction of multiple stained histology images.</a> Journal of Pathology Informatics. 4 (2), 7 (2013).</li><li>Shojaii, R., Karavardanyan, T., Yaffe, M., Martel, A. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Validation+of+histology+image+registration.">Validation of histology image registration.</a> SPIE Medical Imaging. 7962, 79621E, doi:10.1117/12.878762. 7962 (7962E), (2011).</li><li>Ridler, T. W., Calvard, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Picture+thresholding+using+an+iterative+selection+method.">Picture thresholding using an iterative selection method.</a> IEEE Transactions on Systems, Man, and Cybernetics. 8 (8), 630-632 (1978).</li><li>Freeman, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Computer+processing+of+line-drawing+images.">Computer processing of line-drawing images.</a> ACM Computing Surveys (CSUR. 6 (1), 57-97 (1974).</li><li>Giardina, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Accuracy+of+curve+approximation+by+harmonically+related+vectors+with+elliptical+loci).">Accuracy of curve approximation by harmonically related vectors with elliptical loci).</a> Computer Graphics and Image Processing. 6 (3), 277-285 (1977).</li><li>Shojaii, R., Martel, A. 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+novel+edge+point+selection+method+for+registration+of+histology+images.">A novel edge point selection method for registration of histology images.</a> Optical Tissue Image analysis in Microscopy, Histopathology and Endoscopy. (OPTIMHisE) Workshop, MICCAI. , (2009).</li><li>Besl, P., McKay, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+method+for+registration+of+3-D+shapes.">A method for registration of 3-D shapes.</a> IEEE Transactions on Pattern Analysis and Machine Intelligence. 14 (2), 239-256 (1992).</li><li>Chatterjee, S., 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=Loss+of+Igfbp7+causes+precocious+involution+in+lactating+mouse+mammary+gland.">Loss of Igfbp7 causes precocious involution in lactating mouse mammary gland.</a> PLoS ONE. 9 (2), e87858 (2013).</li><li>Manjunath, B. S., Chellappa, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Unsupervised+texture+segmentation+using+Markov+random+field+models.">Unsupervised texture segmentation using Markov random field models.</a> IEEE Transactions on Pattern Analysis and Machine Intelligence. 13 (5), 478-482 (1991).</li><li>Krishnamachari, S., Chellappa, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiresolution+Gauss-Markov+random+field+models+for+texture+segmentation.">Multiresolution Gauss-Markov random field models for texture segmentation.</a> IEEE Transactions on Image Processing: a publication of the IEEE Signal Processing Society. 6 (2), 251-267 (1997).</li></ol>

The authors have nothing to disclose

In this study, we have developed an image registration workflow to reconstruct a 3D histology volume from serial 2D histology images, which does not require internal randomly selected landmarks or implanted fiducial markers within the tissue, which might distort the tissue. By the method described, optical blockface images themselves are used as the reference images prior to sectioning. We use external holes drilled in the paraffin block to aid in aligning the blockface images and to correct for the 2D transversal moveme...

IGFBP7 (insulin like growth factor binding protein 7) is a member of the IGF-binding protein family, and has been shown to bind the IGF1 receptor4. Down-regulation of IGFBP7 is known to be correlated with poor prognosis in breast cancer5, while the reintroduction of IGFBP7 in Xenograft tumor models greatly inhibits the tumors growth6 through induction of apoptosis and cellular senescence7. In order to study the effects of IGFPB7, an Igfbp7-null mouse was created5 (unpublished data). While these mice do not develop tumors, they show changes in histology of the ovary, muscle and liver as well as defects in mammary gland developmental patterning (unpublished data). The defective phenotype was first indicated as the null mice have smaller litter sizes and are unable to sustain multiple large litters (unpublished data).
3D histology volumes have the potential to provide useful information for quantitative and comparative analyses and assessment of pathologic findings in volumetric medical images. Three-dimensional confocal, two-photon microscopy can provide high-resolution cell morphological information of the gland at local extent14 , but it has a limited field of view and depth. Histology volume reconstruction provides more information over a much greater spatial extent. Using traditional approaches some distortion is anticipated during the preparation of histological sections, such as shrinkage, expansion, tears, and folds. These distortions make it difficult to register serial histological images into a 3D stack to reconstruct a 3D volume. As the number of consecutive sections with defects increases the similarities between intact sections is reduced and consequently makes the registration process more complicated.
Different methods have been proposed to register histological sections and to create a continuous histology volume. Some techniques depend on intensity variations8, and others are based on the shape of the sections9. For some specimens the anatomical structures can be used as landmarks10,11 along with landmark-based registration methods12,13. But these internal structures might not be detectable throughout the whole volume and for some specimens no reliable anatomical structures can be identified. Some groups have used a pair-wise registration approach and registered consecutive histology images one to another using contours or anatomical structures16-18. Registering serial histology sections to one another without the use of reference images may propagate registration error and change the actual shape of the histology volume. Pair-wise registration approach relies on the consistency of shape of the histology sections and the internal structures throughout the stack of the images; therefore it requires dense sampling of the specimen, which might not always possible, e.g., for clinical specimens.
In this pipeline we use blockface images as a set of reference images for histology volume reconstruction19. Blockface images are taken of the paraffin tissue blocks after mounting on the microtome and before each section is cut. Thus, damage to individual serial sections cut does not interfere with registration of serial sections8,11,15. We capture the blockface images in a different way from the other groups. The optical block face images are obtained by a telecentric lens to eliminate or minimize the barrel and perspective distortion, which usually occurs when using regular lenses in optics. This is one of the advantages of the proposed approach over the other published methods, which perform blockface imaging using regular lenses. The images are taken at a slight oblique angle to use the reflection of the surface of the block for contrast enhancement between the tissue and paraffin surface and to eliminate the shadow of the tissue in depth, under the paraffin surface. A photographic filter is also used to polarize the light coming from the block surface and the tissue to balance the contrast19. To correct for the displacement of the block on the rotary microtome, two to three holes are drilled in the corners of the block, which are easily detectable in the blockface images. The centroids of these holes are used along with landmark-based rigid registration to align the blockface images.

<table border="0" cellpadding="0" cellspacing="0" width="852">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:260px;">16% PFA</td>
			<td style="width:179px;">VWR International</td>
			<td style="width:119px;">15710</td>
			<td style="width:295px;">16% Paraformaldehyde solution</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:260px;">Small tissue processing cassettes</td>
			<td style="width:179px;">VWR International</td>
			<td>CA95029-956</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:260px;">Leica ASP300 Automated Tissue processor</td>
			<td style="width:179px;">Leica</td>
			<td>14047643515</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:260px;">100% ethanol</td>
			<td style="width:179px;">Fisher Scientific</td>
			<td style="width:119px;">S25307B</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:260px;">Xylene</td>
			<td>VWR International&#160;</td>
			<td>CA95057-822</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:260px;">Paraffin&#160;</td>
			<td style="width:179px;">Thermo Fisher</td>
			<td style="width:119px;">39501006</td>
			<td>Paraplast Tissue Embedding Medium</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:260px;">Leica EG 1160 Embedding Centre</td>
			<td style="width:179px;">Leica</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:260px;">Leica rotary microtome</td>
			<td style="width:179px;">Leica</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:260px;">Milling machine</td>
			<td style="width:179px;">Argo</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:260px;">Microscope slides</td>
			<td style="width:179px;">VWR International&#160;</td>
			<td>CA48312-015</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:260px;">H&#38;E stain</td>
			<td style="width:179px;">VWR International</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:260px;">Automatic stainer</td>
			<td style="width:179px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:260px;">Coverslips&#160;</td>
			<td style="width:179px;">VWR International&#160;</td>
			<td>48404-452</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:260px;">MEDITE RCM 7000 Glass Coverslipper</td>
			<td style="width:179px;">MEDITE</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:260px;">Leica SCN400 slide scanner</td>
			<td style="width:179px;">Leica</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:260px;">MATLAB</td>
			<td style="width:179px;">MathWorks Inc</td>
			<td>MATLAB 2007b</td>
			<td>Development software</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:260px;">MeVisLab</td>
			<td style="width:179px;">MeVis Medical Solutions AG</td>
			<td>MeVisLab 2.1</td>
			<td>3D visualization software</td>
		</tr>
	</tbody>
</table>

reconstruction of 3-dimensional histology volume and its application to study mouse mammary glands

Histology volume reconstruction facilitates the study of 3D shape and volume change of an organ at the level of macrostructures made up of cells. It can also be used to investigate and validate novel techniques and algorithms in volumetric medical imaging and therapies. Creating 3D high-resolution atlases of different organs1,2,3 is another application of histology volume reconstruction. This provides a resource for investigating tissue structures and the spatial relationship between various cellular features. We present an image registration approach for histology volume reconstruction, which uses a set of optical blockface images. The reconstructed histology volume represents a reliable shape of the processed specimen with no propagated post-processing registration error. The Hematoxylin and Eosin (H&#38;E) stained sections of two mouse mammary glands were registered to their corresponding blockface images using boundary points extracted from the edges of the specimen in histology and blockface images. The accuracy of the registration was visually evaluated. The alignment of the macrostructures of the mammary glands was also visually assessed at high resolution.
This study delineates the different steps of this image registration pipeline, ranging from excision of the mammary gland through to 3D histology volume reconstruction. While 2D histology images reveal the structural differences between pairs of sections, 3D histology volume provides the ability to visualize the differences in shape and volume of the mammary glands.

A pitfall of traditional microscopy techniques is that the understanding of an organ at the microscopic level is limited to one field-of-view at a time. Even &#8220;total disclosure&#8221; slides, which provide entire slide sections, fail to provide three-dimensional information. With the development of whole slide, dynamic scanning technologies, our ability to see a section in its entirety has increased, however extrapolating structures requires 3D histology volume reconstruction.
To better c...

Watch this Scientific Journal Video about Reconstruction of 3-Dimensional Histology Volume and its Application to Study Mouse Mammary Glands at JoVE.com

Reconstruction of 3-Dimensional Histology Volume and its Application to Study Mouse Mammary Glands

We present an image registration approach for 3-dimensional (3D) histology volume reconstruction, which facilitates the study of the changes of an organ at the level of macrostructures made up of cells . Using this approach, we studied the 3D changes between wild-type and Igfbp7-null mammary glands.

Histology volume reconstruction facilitates the study of 3D shape and volume change of an organ at the level of macrostructures made up of cells. It can ...

reconstruction-3-dimensional-histology-volume-its-application-to

Research

JoVE Journal

Biology

14.3K Views.  University of Toronto. We present an image registration approach for 3-dimensional (3D) histology volume reconstruction, which facilitates the study of the changes of an organ at the level of macrostructures made up of cells . Using this approach, we studied the 3D changes between wild-type and Igfbp7-null mammary glands. 

Video: Reconstruction of 3-Dimensional Histology Volume and its Application to Study Mouse Mammary Glands

Testing Visual Sensitivity to the Speed and Direction of Motion in Lizards

Testing visual sensitivity in any species provides basic information regarding behaviour, evolution, and ecology. However, testing specific features of the visual system provide more empirical evidence for functional applications. Investigation into the sensory system provides information about the sensory capacity, learning and memory ability, and establishes known baseline behaviour in which to gauge deviations (Burghardt, 1977). However, unlike mammalian or avian systems, testing for learning and memory in a reptile species is difficult. Furthermore, using an operant paradigm as a psychophysical measure of sensory ability is likewise as difficult. Historically, reptilian species have responded poorly to conditioning trials because of issues related to motivation, physiology, metabolism, and basic biological characteristics. Here, I demonstrate an operant paradigm used a novel model lizard species, the Jacky dragon (Amphibolurus muricatus) and describe how to test peripheral sensitivity to salient speed and motion characteristics. This method uses an innovative approach to assessing learning and sensory capacity in lizards. I employ the use of random-dot kinematograms (RDKs) to measure sensitivity to speed, and manipulate the level of signal strength by changing the proportion of dots moving in a coherent direction. RDKs do not represent a biologically meaningful stimulus, engages the visual system, and is a classic psychophysical tool used to measure sensitivity in humans and other animals. Here, RDKs are displayed to lizards using three video playback systems. Lizards are to select the direction (left or right) in which they perceive dots to be moving. Selection of the appropriate direction is reinforced by biologically important prey stimuli, simulated by computer-animated invertebrates.

Testing visual sensitivity in lizards using an operant conditioning paradigm that employs video playback of random-dot kinematograms and computer-generated invertebrates.

Badania wizualne Wrażliwość na prędkość i kierunek ruchu w Jaszczurki

Testing visual sensitivity in any species provides basic information regarding behaviour, evolution, and ecology. However, testing specific features of ...

The Ladder Rung Walking Task: A Scoring System and its Practical Application.

Progress in the development of animal models for/stroke, spinal cord injury, and other neurodegenerative disease requires tests of high sensitivity to elaborate distinct aspects of motor function and to determine even subtle loss of movement capacity. To enhance efficacy and resolution of testing, tests should permit qualitative and quantitative measures of motor function and be sensitive to changes in performance during recovery periods. The present study describes a new task to assess skilled walking in the rat to measure both forelimb and hindlimb function at the same time. Animals are required to walk along a horizontal ladder on which the spacing of the rungs is variable and is periodically changed. Changes in rung spacing prevent animals from learning the absolute and relative location of the rungs and so minimize the ability of the animals to compensate for impairments through learning. In addition, changing the spacing between the rungs allows the test to be used repeatedly in long-term studies. Methods are described for both quantitative and qualitative description of both fore- and hindlimb performance, including limb placing, stepping, co-ordination. Furthermore, use of compensatory strategies is indicated by missteps or compensatory steps in response to another limb&#x2019;s misplacement. 

The ladder rung walking task is a new test to assess skilled walking and measure both forelimb and hindlimb placing, stepping, and inter-limb co-ordination.

Progress in the development of animal models for/stroke, spinal cord injury, and other neurodegenerative disease requires tests of high sensitivity to ...

Lens Transplantation in Zebrafish and its Application in the Analysis of Eye Mutants

The lens plays an important role in the development of the optic cup[1,2]. Using the zebrafish as a model organism, questions regarding lens development can be addressed. The zebrafish is useful for genetic studies due to several advantageous characteristics, including small size, high fecundity, short lifecycle, and ease of care. Lens development occurs rapidly in zebrafish. By 72 hpf, the zebrafish lens is functionally mature [3]. Abundant genetic and molecular resources are available to support research in zebrafish. In addition, the similarity of the zebrafish eye to those of other vertebrates provides basis for its use as an excellent animal model of human defects[4-7]. Several zebrafish mutants exhibit lens abnormalities, including high levels of cell death, which in some cases leads to a complete degeneration of lens tissues [8]. To determine whether lens abnormalities are due to intrinsic causes or to defective interactions with the surrounding tissues, transplantation of a mutant lens into a wild-type eye is performed. Using fire-polished metal needles, mutant or wild-type lenses are carefully dissected from the donor animal, and transferred into the host. To distinguish wild-type and mutant tissues, a transgenic line is used as the donor. This line expresses membrane-bound GFP in all tissues, including the lens. This transplantation technique is an essential tool in the studies of zebrafish lens mutants.

Lens development involves interactions with other tissues. Several zebrafish eye mutants are characterized by an abnormally small lens size. Here we demonstrate a lens transplantation experiment to determine whether this phenotype is due to intrinsic causes or defective interactions with tissues that surround the lens.

The lens plays an important role in the development of the optic cup[1,2]. Using the zebrafish as a model organism, questions regarding lens development ...

Mouse Mammary Epithelial Cells form Mammospheres During Lactogenic Differentiation

A phenotypic measure commonly used to determine the degree of lactogenic differentiation in mouse mammary epithelial cell cultures is the formation of dome shaped cell structures referred to as mammospheres 1. The HC11 cell line has been employed as a model system for the study of regulation of mammary lactogenic differentiation both in vitro and in vivo 2. The HC11 cells differentiate and synthesize milk proteins in response to treatment with lactogenic hormones. Following the growth of HC11 mouse mammary epithelial cells to confluence, lactogenic differentiation was induced by the addition of a combination of lactogenic hormones including dexamethasone, insulin, and prolactin, referred to as DIP. The HC11 cells induced to differentiate were photographed at times up to 120 hours post induction of differentiation and the number of mammospheres that appeared in each culture was enumerated. The size of the individual mammospheres correlates with the degree of differentiation and this is depicted in the images of the differentiating cells.

HC11 lactogenic differentiation can be characterized by the formation of domed structures referred to as mammospheres. The structures can be enumerated by phase contrast microscopy to aid in quantifying lactogenic differentiation.

A phenotypic measure commonly used to determine the degree of lactogenic differentiation in mouse mammary epithelial cell cultures is the formation of ...

Evaluation of Mammary Gland Development and Function in Mouse Models

The human mammary gland is composed of 15-20 lobes that secrete milk into a branching duct system opening at the nipple. Those lobes are themselves composed of a number of terminal duct lobular units made of secretory alveoli and converging ducts1. In mice, a similar architecture is observed at pregnancy in which ducts and alveoli are interspersed within the connective tissue stroma. The mouse mammary gland epithelium is a tree like system of ducts composed of two layers of cells, an inner layer of luminal cells surrounded by an outer layer of myoepithelial cells denoted by the confines of a basement membrane2. At birth, only a rudimental ductal tree is present, composed of a primary duct and 15-20 branches. Branch elongation and amplification start at the beginning of puberty, around 4 weeks old, under the influence of hormones3,4,5. At 10 weeks, most of the stroma is invaded by a complex system of ducts that will undergo cycles of branching and regression in each estrous cycle until pregnancy2. At the onset of pregnancy, a second phase of development begins, with the proliferation and differentiation of the epithelium to form grape-shaped milk secretory structures called alveoli6,7. Following parturition and throughout lactation, milk is produced by luminal secretory cells and stored within the lumen of alveoli. Oxytocin release, stimulated by a neural reflex induced by suckling of pups, induces synchronized contractions of the myoepithelial cells around the alveoli and along the ducts, allowing milk to be transported through the ducts to the nipple where it becomes available to the pups 8. Mammary gland development, differentiation and function are tightly orchestrated and require, not only interactions between the stroma and the epithelium, but also between myoepithelial and luminal cells within the epithelium9,10,11. Thereby, mutations in many genes implicated in these interactions may impair either ductal elongation during puberty or alveoli formation during early pregnancy, differentiation during late pregnancy and secretory activation leading to lactation12,13. In this article, we describe how to dissect mouse mammary glands and assess their development using whole mounts. We also demonstrate how to evaluate myoepithelial contractions and milk ejection using an ex-vivo oxytocin-based functional assay. The effect of a gene mutation on mammary gland development and function can thus be determined in situ by performing these two techniques in mutant and wild-type control mice.

This method describes how to dissect and assess mammary gland development and function from mice. Excised mammary glands are assessed for the degree of development using whole mount while milk ejection is evaluated using an oxytocin-based myoepithelial cell contraction assay.

The human mammary gland is composed of 15-20 lobes that secrete milk into a branching duct system opening at the nipple. Those lobes are themselves ...

Intraductal Injection for Localized Drug Delivery to the Mouse Mammary Gland

Herein we describe a protocol to deliver various reagents to the mouse mammary gland via intraductal injections. Localized drug delivery and knock-down of genes within the mammary epithelium has been difficult to achieve due to the lack of appropriate targeting molecules that are independent of developmental stages such as pregnancy and lactation. Herein, we describe a technique for localized delivery of reagents to the mammary gland at any stage in adulthood via intraductal injection into the nipples of mice. The injections can be performed on live mice, under anesthesia, and allow for a non-invasive and localized drug delivery to the mammary gland. Furthermore, the injections can be repeated over several months without damaging the nipple. Vital dyes such as Evans Blue are very helpful to learn the technique. Upon intraductal injection of the blue dye, the entire ductal tree becomes visible to the eye. Furthermore, fluorescently labeled reagents also allow for visualization and distribution within the mammary gland. This technique is adaptable for a variety of compounds including siRNA, chemotherapeutic agents, and small molecules.

A protocol for the non-invasive intraductal delivery of aqueous reagents to the mouse mammary gland is described. The method takes advantage of localized injection into the nipples of mammary glands targeting mammary ducts specifically. This technique is adaptable for a variety of compounds including siRNA, chemotherapeutic agents and small molecules.

Herein we describe a protocol to deliver various reagents to the mouse mammary gland via intraductal injections. Localized drug delivery and knock-down of ...

A Fluorescence-based Exonuclease Assay to Characterize DmWRNexo, Orthologue of Human Progeroid WRN Exonuclease, and Its Application to Other Nucleases

WRN exonuclease is involved in resolving DNA damage that occurs either during DNA replication or following exposure to endogenous or exogenous genotoxins. It is likely to play a role in preventing accumulation of recombinogenic intermediates that would otherwise accumulate at transiently stalled replication forks, consistent with a hyper-recombinant phenotype of cells lacking WRN. In humans, the exonuclease domain comprises an N-terminal portion of a much larger protein that also possesses helicase activity, together with additional sites important for DNA and protein interaction. By contrast, in Drosophila, the exonuclease activity of WRN (DmWRNexo) is encoded by a distinct genetic locus from the presumptive helicase, allowing biochemical (and genetic) dissection of the role of the exonuclease activity in genome stability mechanisms. Here, we demonstrate a fluorescent method to determine WRN exonuclease activity using purified recombinant DmWRNexo and end-labeled fluorescent oligonucleotides. This system allows greater reproducibility than radioactive assays as the substrate oligonucleotides remain stable for months, and provides a safer and relatively rapid method for detailed analysis of nuclease activity, permitting determination of nuclease polarity, processivity, and substrate preferences.

Exonucleases play critical roles in ensuring genome stability. Loss of WRN exonuclease function results in premature aging. Studying substrates and other requirements of the nuclease in vitro can help elucidate its role in vivo. Here we demonstrate a rapid and reproducible fluorescence-based assay to measure its nuclease activity.

WRN exonuclease is involved in resolving DNA damage that occurs either during DNA replication or following exposure to endogenous or exogenous genotoxins. ...

High-throughput Image Analysis of Tumor Spheroids: A User-friendly Software Application to Measure the Size of Spheroids Automatically and Accurately

The increasing number of applications of three-dimensional (3D) tumor spheroids as an in vitro model for drug discovery requires their adaptation to large-scale screening formats in every step of a drug screen, including large-scale image analysis. Currently there is no ready-to-use and free image analysis software to meet this large-scale format. Most existing methods involve manually drawing the length and width of the imaged 3D spheroids, which is a tedious and time-consuming process. This study presents a high-throughput image analysis software application &#8211; SpheroidSizer, which measures the major and minor axial length of the imaged 3D tumor spheroids automatically and accurately; calculates the volume of each individual 3D tumor spheroid; then outputs the results in two different forms in spreadsheets for easy manipulations in the subsequent data analysis. The main advantage of this software is its powerful image analysis application that is adapted for large numbers of images. It provides high-throughput computation and quality-control workflow. The estimated time to process 1,000 images is about 15 min&#160;on a minimally configured laptop, or around 1 min&#160;on a multi-core performance workstation. The graphical user interface (GUI) is also designed for easy quality control, and users can manually override the computer results. The key method used in this software is adapted from the active contour algorithm, also known as Snakes, which is especially suitable for images with uneven illumination and noisy background that often plagues automated imaging processing in high-throughput screens. The complimentary &#8220;Manual Initialize&#8221; and &#8220;Hand Draw&#8221; tools provide the flexibility to SpheroidSizer in dealing with various types of spheroids and diverse quality images. This high-throughput image analysis software remarkably reduces labor and speeds up the analysis process. Implementing this software is beneficial for 3D tumor spheroids to become a routine in vitro model for drug screens in industry and academia.

We present a high-throughput image analysis software application to measure the size of three-dimensional tumor spheroids imaged with bright-field microscopy. This application provides a fast and effective way to examine the effects of therapeutic drugs on spheroids, which is beneficial for researchers who wish to use spheroids in drug screens.

The increasing number of applications of three-dimensional (3D) tumor spheroids as an in vitro model for drug discovery requires their adaptation to ...

Using Mouse Mammary Tumor Cells to Teach Core Biology Concepts: A Simple Lab Module

Undergraduate biology students are required to learn, understand and apply a variety of cellular and molecular biology concepts and techniques in preparation for biomedical, graduate and professional programs or careers in science. To address this, a simple laboratory module was devised to teach the concepts of cell division, cellular communication and cancer through the application of animal cell culture techniques. Here the mouse mammary tumor (MMT) cell line is used to model for breast cancer. Students learn to grow and characterize these animal cells in culture and test the effects of traditional and non-traditional chemotherapy agents on cell proliferation. Specifically, students determine the optimal cell concentration for plating and growing cells, learn how to prepare and dilute drug solutions, identify the best dosage and treatment time course of the antiproliferative agents, and ascertain the rate of cell death in response to various treatments. The module employs both a standard cell counting technique using a hemocytometer and a novel cell counting method using microscopy software. The experimental procedure lends to open-ended inquiry as students can modify critical steps of the protocol, including testing homeopathic agents and over-the-counter drugs. In short, this lab module requires students to use the scientific process to apply their knowledge of the cell cycle, cellular signaling pathways, cancer and modes of treatment, all while developing an array of laboratory skills including cell culture and analysis of experimental data not routinely taught in the undergraduate classroom.

A feasible laboratory module for biology undergraduates that explores advanced cellular and molecular concepts using animal cell culture is described. Students grow, characterize and manipulate a breast cancer cell model by exposure to chemotherapy agents. Cell viability is assayed through cell counting using both a standard and novel method.

Undergraduate biology students are required to learn, understand and apply a variety of cellular and molecular biology concepts and techniques in ...

Measuring Pressure Volume Loops in the Mouse

Understanding the causes and progression of heart disease presents a significant challenge to the biomedical community. The genetic flexibility of the mouse provides great potential to explore cardiac function at the molecular level. The mouse&#39;s small size does present some challenges in regards to performing detailed cardiac phenotyping. Miniaturization and other advancements in technology have made many methods of cardiac assessment possible in the mouse. Of these, the simultaneous collection of pressure and volume data provides a detailed picture of cardiac function that is not available through any other modality. Here a detailed procedure for the collection of pressure-volume loop data is described. Included is a discussion of the principles underlying the measurements and the potential sources of error. Anesthetic management and surgical approaches are discussed in great detail as they are both critical to obtaining high quality hemodynamic measurements. The principles of hemodynamic protocol development and relevant aspects of data analysis are also addressed.

This manuscript describes a detailed protocol for the collection of pressure-volume data from the mouse.

Understanding the causes and progression of heart disease presents a significant challenge to the biomedical community. The genetic flexibility of the ...