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. Espécimen <ol><li> Impuestos especiales de las glándulas mamarias quirúrgicamente de tipo salvaje CDH1 así como los ratones IGFBP7 nulo tres días publican inicio de la lactancia. </li><li> Separe las glándulas en portaobjetos de vidrio para ayudar a recuperar la morfología de la glándula mamaria nativo. </li></ol> 2. La fijación y procesamiento de tejidos <ol><li> Fijar las glándulas mamarias en neutro tamponado al 4% PFA O / N a 4 ° C. </li><li> Guarde las glándulas en etanol al 70% antes de la elaboración de tejidos. </li><li> Transferir las glándulas para pequeños casetes de procesamiento de tejidos. </li><li> Procesar los tejidos usando un procesador automatizado de tejido <ol><li> Deshidratar los tejidos en el aumento de etanol y xileno baños de etanol al 70% durante 45 minutos, 2 veces en etanol al 95% durante 45 min, 3 veces en etanol al 100% durante 1 hora y 2 veces en xileno durante 45 min. </li><li> Permear los tejidos con parafina 3 veces durante 1 hora cada uno en el vacío con la presión aplicada. </li></ol></li><li> Incrustar los tejidos en parafina para formar bloques, Para seccionar. </li></ol> 3. Histología y Blockface Imaging <ol><li> Recorte los bloques de parafina utilizando un micrótomo rotatorio hasta que se elimina el exceso de parafina. </li><li> Use una máquina de fresado vertical para perforar agujeros de 1 mm en al menos dos esquinas del bloque de parafina perpendicular a la casete. </li><li> Monte el bloque de tejido en el micrótomo rotatorio. </li><li> Establecer el sistema de formación de imágenes 19 blockface delante del microtomo. </li><li> Captura de imagen blockface óptica antes de seccionar. </li><li> Cortar las cintas de cuatro secciones a las 5 micras de espesor en el microtomo. <ol><li> Transfiera las cintas para el baño de agua fría. </li><li> Separar las segunda y cuarta secciones de la cinta y montarlos en portaobjetos de microscopio. La elección de las segunda y cuarta secciones proporciona una brecha de 5 m entre las secciones. </li><li> Amplíe cada sección en un baño de agua caliente (48 º C) para desarrugar, luego volver a montarlo en el portaobjetos de un microscopio. NOTA: CUtting, montaje, unwrinkling las secciones causan algunas distorsiones en la sección, como desgarro, doblez, la contracción y la expansión. Estos artefactos complican el registro de las secciones histológicas. </li><li> Teñir las secciones con H &amp; E utilizando una tinción automática. </li><li> Cubreobjetos las diapositivas usando un cubreobjetos automático. </li><li> Digitalizar las diapositivas usando un escáner de diapositivas histología digital en la resolución de su interés. Para este protocolo el aumento es de 20x y una resolución de 0,47 micras. </li><li> Down-muestra las imágenes de histología a la resolución de las imágenes blockface, 18 micras. </li></ol></li></ol> 4. Registro de Imágenes <ol><li> Segmentación de imagen y el punto de selección <ol><li> En blockface imágenes miden los valores de píxeles de los orificios de registro y utilizar el valor medio como un umbral fijo al segmento de los orificios de registro en las esquinas del bloque de parafina. </li><li> Dado que algunas partes adicionales también pueden ser segmentados porutilizando el umbral fijo, utilizar la circularidad y el área de los objetos segmentados para encontrar los agujeros y descartar los objetos adicionales. Para hacer esto, escriba un pequeño código y encontrar la relación de (4π x área) / (perímetro) 2 para los objetos segmentados. Esta relación de objetos redondos es de 1. </li><li> Para cada glándula mamaria, seleccionar una imagen blockface como referencia y alinear el resto de las imágenes blockface a la referencia utilizando el centro de los orificios de registro y técnicas de registro basado en la señal. </li><li> Para las imágenes blockface alineados, segmento manualmente o extraer el tejido del fondo. Utilice el objeto más importante en la máscara para el resto del protocolo. </li><li> Para H &amp; E secciones siguen los siguientes pasos para la segmentación automática. <ol><li> Utilice una técnica de umbralización Otsu 20 a las imágenes del segmento de los antecedentes y crear máscaras binarias de las imágenes de histología. </li><li> Identificar y seleccionar el objeto más importante en cada máscara utilizando la histogram de los objetos etiquetados. </li><li> Extraiga los puntos de los límites de ancho de un píxel, tanto de la histología y máscaras blockface. </li><li> Utilice el algoritmo de código de cadena 21, para representar los puntos de los límites de una secuencia de tramos lineales se ajusta. </li></ol></li></ol></li><li> Registro rígido inicial <ol><li> Utilice Fourier Descriptores algoritmo 22, para encontrar el rígido inicial transformada entre los puntos de los límites de la histología y sus imágenes blockface correspondientes. Esta inicial incluye transformar los factores de traslación, rotación y escala. </li><li> Transformar cada imagen histología con la inicial transformada obtenido de la etapa anterior. </li></ol></li><li> Refinamiento del registro rígido <ol><li> Retire las secciones altas borde curvatura del contorno histología utilizando un filtro de balanceo de la bola 23. </li><li> Seleccione 500 puntos de los puntos de los límites de histología restantes utilizando aleatoriamente distribución uniforme. </li><li> Transformar el delhistología puntos limítrofes al azar con la transformación inicial obtenida a partir de los descriptores de Fourier. </li><li> Seleccione el conjunto de blockface puntos de los límites y el uso iterativos puntos más cercanos (ICP) del algoritmo 24 para encontrar la transformación rígida entre los puntos de los límites blockface, el destino y la histología puntos limítrofes aleatorios. </li><li> Transformar las imágenes de histología alineados obtenidos de la etapa anterior y la pila de imágenes de histología alineados crea el volumen histología. </li><li> Utilice un software de visualización 3D para crear una imagen visual del volumen histología. </li></ol></li><li> Visualización de la Pila de imágenes con un aumento de 5x <ol><li> Down-muestrear las imágenes histológicas originales a 5x de aumento. </li><li> Recortar la región de interés en una de las imágenes de histología. </li><li> Calcular la ubicación de esa región en otras imágenes de histología 5x utilizando la combinación de las transformaciones rígidas de los dos pasos de registro. </li><li> Recortar la regiComplementos de interés a la misma región de tamaño en todas las demás imágenes de histología. </li><li> Finalmente refinar el alineamiento entre las regiones de forma manual. Escriba un programa que se superpone dos imágenes y permite la selección de los valores de rotación y traslación de una de las imágenes más de la otra y luego guarda la imagen transformada cuando se acepta la alineación. </li><li> Ver las pilas de las regiones de histología 5x alineados utilizando un software de visualización 3D. </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

En este estudio, hemos desarrollado un flujo de trabajo de registro de imágenes para reconstruir un volumen histología en 3D a partir de imágenes de histología en 2D de serie, que no requieren puntos de referencia internos seleccionados al azar o marcadores fiduciales implantados dentro del tejido, que puedan distorsionar el tejido. Mediante el método descrito, imágenes blockface ópticos mismos se utilizan como imágenes de referencia antes de seccionar. Utilizamos orificios externos perforados en el bloque de pa...

IGFBP7 (la insulina como factor de crecimiento de la proteína de unión a 7) es un miembro de la familia de proteínas de unión de IGF-, y se ha demostrado que se unen al receptor de IGF1 4. Down-regulación de IGFBP7 se sabe que se correlaciona con mal pronóstico en cáncer de mama 5, mientras que la reintroducción de IGFBP7 en modelos de tumores de xenoinjertos inhibe en gran medida los tumores de crecimiento 6 a través de la inducción de la apoptosis y senescencia celular 7. Con el fin de estudiar los efectos de IGFPB7, un ratón-IGFBP7 nula fue creado 5 (datos no publicados). Mientras que estos ratones no desarrollan tumores, que muestran cambios en la histología del ovario, músculo y el hígado, así como defectos en los patrones de desarrollo de la glándula mamaria (datos no publicados). El fenotipo defectuoso fue indicado por primera vez como los ratones nulos tienen camadas más pequeñas y no son capaces de sostener múltiples camadas grandes (datos no publicados). Volúmenes de histología en 3D tienen el potencial de proporcionar Informat útilion para los análisis cuantitativos y comparativos y la evaluación de los hallazgos patológicos en las imágenes médicas volumétricas. Confocal tridimensional, la microscopía de dos fotones puede proporcionar células de alta resolución información morfológica de la glándula en extensión local 14, pero tiene un campo de visión limitado y profundidad. Reconstrucción volumen Histología proporciona más información sobre un mucho mayor extensión espacial. El uso de los enfoques tradicionales se prevé cierta distorsión durante la preparación de los cortes histológicos, tales como contracción, expansión, las lágrimas, y los pliegues. Estas distorsiones hacen que sea difícil para registrar imágenes histológicas de serie en una pila 3D para reconstruir un volumen 3D. Como el número de secciones consecutivas con defectos aumenta las similitudes entre las secciones intactas se reduce y por lo tanto hace que el proceso de registro más complicado. Se han propuesto diferentes métodos para registrar las secciones histológicas y para crear un VO histología continuolume. Algunas técnicas dependen de variaciones de intensidad 8, y otros se basan en la forma de las secciones 9. Para algunas muestras de las estructuras anatómicas se pueden utilizar como puntos de referencia 10,11, junto con métodos de registro basado-hito 12,13. Pero estas estructuras internas podrían no ser detectables a través de todo el volumen y para algunos especímenes no hay estructuras anatómicas confiables pueden ser identificados. Algunos grupos han utilizado un enfoque de registro de pares y registrado histología imágenes consecutivas de uno a otro utilizando contornos o estructuras anatómicas 16-18. Registro de secciones histológicas de serie el uno al otro sin el uso de imágenes de referencia puede propagar error de registro y cambiar la forma real del volumen de la histología. Enfoque de registro por pares se basa en la consistencia de la forma de las secciones de histología y las estructuras internas a lo largo de la pila de las imágenes; por lo tanto, requiere densa de muestreo de la muestra, la cualno siempre es posible, por ejemplo, para las muestras clínicas. En este gasoducto utilizamos imágenes blockface como un conjunto de imágenes de referencia para la reconstrucción del volumen histología 19. Imágenes Blockface se toman de los bloques de parafina de tejidos después de su montaje en el microtomo y antes se corta cada sección. Por lo tanto, el daño a individuo corte secciones en serie no interfiere con el registro de las secciones de serie 8,11,15. Capturamos las imágenes blockface de una manera diferente a los otros grupos. Las imágenes de la cara del bloque óptico se obtienen mediante un objetivo telecéntrico para eliminar o minimizar el cañón y la perspectiva de la distorsión, que generalmente ocurre cuando se utilizan objetivos regulares en la óptica. Esta es una de las ventajas del enfoque propuesto sobre los otros métodos publicados, que realizan de imágenes blockface usando lentes regulares. Las imágenes son tomadas en un ángulo oblicuo de leve a utilizar la reflexión de la superficie del bloque para el aumento del contraste entre el TISSsuperficie UE y de parafina y para eliminar la sombra del tejido en profundidad, bajo la superficie de parafina. Un filtro fotográfica también se utiliza para polarizar la luz procedente de la superficie del bloque y el tejido para equilibrar el contraste 19. Para corregir para el desplazamiento del bloque en el micrótomo rotatorio, de dos a tres agujeros son perforados en las esquinas del bloque, que son fácilmente detectables en las imágenes blockface. Los centroides de estos agujeros se utilizan junto con el registro rígido basado en hito para alinear las imágenes blockface.

<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

Reconstrucción volumen Histología facilita el estudio de la forma 3D y el cambio de volumen de un órgano a nivel de macro-estructuras formadas por células. También se puede utilizar para investigar y validar nuevas técnicas y algoritmos en imágenes médicas volumétrica y terapias. La creación de los atlas 3D de alta resolución de los diferentes órganos 1,2,3 es otra aplicación de la reconstrucción del volumen histología. Esto proporciona un recurso para la investigación de las estructuras de tejido y la relación espacial entre diferentes características celulares. Presentamos un método de registro de imágenes para la reconstrucción del volumen histología, que utiliza un conjunto de imágenes blockface ópticos. El volumen histología reconstruida representa una forma fiable de la muestra procesada sin error de registro post-procesamiento propagado. Los hematoxilina y eosina (H &amp; E) manchadas secciones de dos glándulas mamarias de ratón se registraron a sus imágenes blockface correspondientes utilizando puntos de los límites extraídos del edbios de la muestra en la histología y blockface imágenes. La precisión del registro se evaluó visualmente. La alineación de las macroestructuras de las glándulas mamarias también se evaluó visualmente en alta resolución. Este estudio delinea las diferentes etapas de esta tubería de registro de imágenes, que van desde la escisión de la glándula mamaria a través de volumen histología reconstrucción 3D. Mientras que las imágenes de histología 2D revelan las diferencias estructurales entre pares de secciones, el volumen de la histología en 3D proporciona la capacidad de visualizar las diferencias en la forma y el volumen de las glándulas mamarias.

Una trampa de técnicas de microscopía tradicionales es que la comprensión de un órgano a nivel microscópico se limita a un campo de visión a la vez. Incluso diapositivas &quot;en total conformidad&quot;, que ofrecen secciones enteras de diapositivas, no proporcionan información tridimensional. Con el desarrollo de la diapositiva entera, tecnologías de análisis dinámicos, nuestra capacidad de ver una sección en su totalidad se ha incrementado, sin embargo la extrapolación de las estructuras requiere volumen h...

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.

Reconstrucción de 3-Dimensional Volumen Histología y su aplicación al estudio del ratón glándulas mamarias

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 vistas.  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.

Prueba de sensibilidad visual a la velocidad y dirección del movimiento en lagartos

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

Investigación

Biología

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.

El peldaño de la escalera a pie de la tarea: un sistema de puntuación y su aplicación práctica.

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.

Trasplante de lentes en el pez cebra y su aplicación en el análisis de mutantes de ojos

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.

Células epiteliales mamarias de ratón forma Mammospheres durante la diferenciación lactogénica

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.

Evaluación de la glándula mamaria de desarrollo y función en modelos de ratón

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.

Inyección intraductal de entrega de la droga localizada a la glándula mamaria de ratón

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. ...

Application of Retinoic Acid to Obtain Osteocytes Cultures from Primary Mouse Osteoblasts

The need for osteocyte cultures is well known to the community of bone researchers; isolation of primary osteocytes is difficult and produces low cell numbers. Therefore, the most widely used cellular system is the osteocyte-like MLO-Y4 cell line.
The method here described refers to the use of retinoic acid to generate a homogeneous population of ramified cells with morphological and molecular osteocyte features.
After isolation of osteoblasts from mouse calvaria, all-trans retinoic acid (ATRA) is added to cell medium, and cell monitoring is conducted daily under an inverted microscope. First morphological changes are detectable after 2 days of treatment and differentiation is generally complete in 5 days, with progressive development of dendrites, loss of the ability to produce extracellular matrix, down-regulation of osteoblast markers and up-regulation of osteocyte-specific molecules.
Daily cell monitoring is needed because of the inherent variability of primary cells, and the protocol can be adapted with minimal variation to cells obtained from different mouse strains and applied to transgenic models. 
The method is easy to perform and does not require special instrumentation, it is highly reproducible, and rapidly generates a mature osteocyte population in complete absence of extracellular matrix, allowing the use of these cells for unlimited biological applications.

Treatment of primary mouse osteoblasts with retinoic acid produces a homogeneous population of ramified cells bearing morphological and molecular features of osteocytes. The method overcomes the difficulty of obtaining and maintaining primary osteocytes in culture, and can be advantageous to study cells derived from transgenic models.&#160;

La aplicación de ácido retinoico para obtener cultivos de osteocitos principal del ratón osteoblastos

The need for osteocyte cultures is well known to the community of bone researchers; isolation of primary osteocytes is difficult and produces low cell ...

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.

De alto rendimiento de imagen Análisis de esferoides tumorales: una aplicación de software fácil de usar para medir el tamaño de esferoides forma automática y precisa

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

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.

La medición de volumen de bucles de presión en el ratón

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