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> Accise le ghiandole mammarie chirurgicamente da wild-type CDH1 nonché IGFBP7-null mice tre giorni dopo l&#39;instaurarsi della lattazione. </li><li> Stendere le ghiandole su vetrini per contribuire a recuperare nativo della ghiandola mammaria morfologia. </li></ol> 2. Fissazione e Tissue Processing <ol><li> Fissare le ghiandole mammarie in folle tamponata 4% PFA O / N a 4 ° C. </li><li> Conservare le ghiandole in etanolo al 70% prima del trattamento del tessuto. </li><li> Trasferire le ghiandole a piccole cassette di trasformazione del tessuto. </li><li> Elaborare i tessuti utilizzando un processore tessuto automatizzato <ol><li> Disidratare tessuti ascendente etanolo e xilene bagni di etanolo al 70% per 45 minuti, 2 volte in etanolo al 95% per 45 minuti, 3 volte in 100% di etanolo per 1 ora e 2 volte in xilene per 45 min. </li><li> Permeare i tessuti con paraffina 3 volte per 1 ora ogni sotto vuoto con pressione applicata. </li></ol></li><li> Incorporare i tessuti in paraffina per formare blocchi, Per il sezionamento. </li></ol> 3. Istologia ed Blockface Imaging <ol><li> Tagliare i blocchi di paraffina utilizzando un microtomo rotativo fino a quando la paraffina in eccesso viene rimosso. </li><li> Utilizzare una fresatrice verticale per perforare fori di 1 mm in almeno due angoli del blocco di paraffina perpendicolare alla cassetta. </li><li> Montare il blocco tessuto sul microtomo rotativo. </li><li> Impostare il sistema di imaging blockface 19 davanti al microtomo. </li><li> Immagine blockface ottica catturare prima del sezionamento. </li><li> Tagliare i nastri di quattro sezioni a 5 micron di spessore sul microtomo. <ol><li> Trasferire i nastri al bagno di acqua fredda. </li><li> Separare la seconda e la quarta sezione del nastro e montarli su vetrini da microscopio. Scegliendo la seconda e la quarta sezione fornisce un divario tra 5 micron sezioni. </li><li> Espandere ciascuna sezione in un bagno di acqua calda (48 ° C) per unwrinkle esso, poi ri-montarlo sul vetrino da microscopio. NOTA: CUtting, montaggio, unwrinkling sezioni causare alcune distorsioni della sezione, come la lacrima, piega, restringimento e l&#39;espansione. Questi manufatti complicano la registrazione delle sezioni istologici. </li><li> Macchiare le sezioni con H &amp; E con un Stainer automatico. </li><li> I vetrini coprioggetto utilizzando un montavetrini automatico. </li><li> Digitalizzare le diapositive utilizzando uno scanner diapositiva istologia digitale alla risoluzione di interesse. Per questo protocollo è l&#39;ingrandimento 20x e la risoluzione è 0.47 micron. </li><li> Down-campionare le immagini istologici per la risoluzione delle immagini blockface, 18 micron. </li></ol></li></ol> 4. Immagine registrazione <ol><li> Immagine Segmentazione e punto di selezione <ol><li> In blockface immagini misurano i valori di pixel dei fori di registrazione e usa il valore medio come una soglia fissa per segmentare i fori di registrazione negli angoli del blocco di paraffina. </li><li> Da alcune parti aggiuntive potrebbero anche essere segmentati dacon il limite fissato, utilizzare la circolarità e l&#39;area degli oggetti segmentati per trovare i buchi ed eliminare gli oggetti extra. Per fare questo, scrivere un piccolo codice e trovare il rapporto di (4π x area) / (perimetro) 2 per gli oggetti segmentati. Questo rapporto per oggetti rotondi è 1. </li><li> Per ogni ghiandola mammaria, selezionare un&#39;immagine blockface come riferimento e allineare il resto delle immagini blockface al riferimento utilizzando il centro dei fori di registrazione e tecniche di registrazione basato limite. </li><li> Per le immagini blockface allineate, segmento manualmente o estrarre il tessuto dallo sfondo. Utilizzare l&#39;oggetto più consistente nella maschera per il resto del protocollo. </li><li> Per H &amp; E sezioni seguire le istruzioni riportate di seguito per la segmentazione automatica. <ol><li> Utilizzare Otsu soglia tecnica 20 alle immagini segmento dallo sfondo e creare maschere binari delle immagini istologici. </li><li> Individuare e selezionare l&#39;oggetto più consistente in ogni maschera usando l&#39;histogram degli oggetti etichettati. </li><li> Estrarre i un pixel di larghezza punti di confine sia da istologia e maschere blockface. </li><li> Utilizzare algoritmo codice catena 21, per rappresentare i punti di confine da una sequenza di lineare a tratti adatta. </li></ol></li></ol></li><li> Registrazione rigida iniziale <ol><li> Utilizzare Fourier descrittori algoritmo 22, per trovare la rigida iniziale trasformazione tra i punti di confine di istologia e le loro immagini blockface corrispondenti. Questo iniziale di trasformare comprende i fattori di conversione, rotazione e scala. </li><li> Trasformare ogni immagine istologia con l&#39;iniziale di trasformazione ottenuto dal passaggio precedente. </li></ol></li><li> Affinamento della registrazione rigido <ol><li> Rimuovere le sezioni ad alta curvatura del bordo dal profilo istologico usando un filtro palla che rotola 23. </li><li> Selezionare 500 punti dei restanti istologici punti di confine in modo casuale con distribuzione uniforme. </li><li> Trasformare il laistologia punti di confine casuali con la trasformazione iniziale ottenuto da descrittori di Fourier. </li><li> Selezionare l&#39;intero insieme di blockface punti di confine e utilizzare iterativi più vicini Points (ICP) 24 algoritmo per trovare la trasformazione rigida tra i punti blockface di confine, di destinazione e di istologia punti di confine casuali. </li><li> Trasforma le immagini istologici allineate ottenuti dalla fase precedente e la pila di immagini di istologia allineate crea il volume istologia. </li><li> Utilizzare un software di visualizzazione 3D per creare una immagine visiva del volume istologia. </li></ol></li><li> Visualizzazione della Pila di immagini a ingrandimento 5x <ol><li> Down-assaggiare le immagini istologici originali a 5x ingrandimento. </li><li> Ritagliare la regione di interesse in una delle immagini istologici. </li><li> Calcolare la posizione di tale regione in altre immagini istologici 5x utilizzando la combinazione delle trasformazioni rigide delle due fasi di registrazione. </li><li> Ritagliare la regions di interesse per la stessa regione dimensioni in tutte le altre immagini di istologia. </li><li> Infine definire l&#39;allineamento tra le regioni manualmente. Scrivere un programma che sovrappone due immagini e permette di selezionare i valori di rotazione e traslazione di una delle immagini sopra l&#39;altra e quindi salva l&#39;immagine trasformata quando l&#39;allineamento è accettata. </li><li> Guarda le pile delle regioni istologici 5x allineati utilizzando un software di visualizzazione 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

In questo studio, abbiamo sviluppato una registrazione workflow un&#39;immagine di ricostruire un volume istologia 3D da immagini seriali istologia 2D, che non richiede punti di riferimento interni scelti a caso o marcatori fiduciali impiantati all&#39;interno del tessuto, che potrebbero distorcere il tessuto. Con il metodo descritto, immagini blockface ottici stessi vengono utilizzati come immagini di riferimento prima del sezionamento. Usiamo fori esterni praticati nel blocco di paraffina per aiutare ad allineare le i...

IGFBP7 (insulina come la proteina legante il fattore di crescita 7) è un membro della famiglia delle proteine ​​IGF-binding, e ha dimostrato di legarsi al recettore IGF1 4. Down-regolazione di IGFBP7 è noto essere correlata con la prognosi nel cancro al seno 5, mentre la reintroduzione del IGFBP7 in modelli di tumore dello xenotrapianto inibisce notevolmente la crescita dei tumori 6 attraverso l&#39;induzione di apoptosi e senescenza cellulare 7. Al fine di studiare gli effetti di IGFPB7, un mouse IGFBP7-null è stato creato 5 (dati non pubblicati). Mentre questi topi non sviluppano tumori, mostrano cambiamenti nella istologia delle ovaie, muscoli e nel fegato, nonché difetti di sviluppo della ghiandola mammaria patterning (dati non pubblicati). Il fenotipo difettoso è stato indicato come i topi nulli hanno dimensioni dei cuccioli più piccoli e sono in grado di sostenere più cucciolate di grandi dimensioni (dati non pubblicati). Volumi di istologia 3D hanno il potenziale di fornire informat utiliion per le analisi quantitative e comparative e la valutazione di risultati patologici in immagini mediche volumetriche. Confocale tridimensionale, microscopia a due fotoni può fornire cellule di alta risoluzione informazioni morfologica della ghiandola alla misura locale 14, ma ha un limitato campo di vista e profondità. Ricostruzione del volume Istologia fornisce ulteriori informazioni su una maggiore estensione spaziale. Utilizzando approcci tradizionali certa distorsione è anticipata durante la preparazione di sezioni istologiche, come il restringimento, espansione, lacrime e pieghe. Queste distorsioni rendono difficile registrare immagini istologiche seriali in una pila 3D per ricostruire un volume 3D. Poiché il numero di sezioni consecutive con difetti aumenta le somiglianze tra sezioni intatte ridotta e conseguentemente rende il processo di registrazione più complicato. Diversi metodi sono stati proposti per registrare sezioni istologiche e per creare un istologia vo continualume. Alcune tecniche dipendono da variazioni di intensità 8, e altri sono basati sulla forma delle sezioni 9. Per alcuni esemplari le strutture anatomiche possono essere utilizzate come punti di riferimento 10,11 insieme basato limite-metodi di registrazione 12,13. Ma queste strutture interne potrebbero non essere rilevabile durante l&#39;intero volume e per alcuni esemplari presenti strutture anatomiche affidabili possono essere identificati. Alcuni gruppi hanno utilizzato un approccio di registrazione pair-wise e registrato le immagini istologia consecutive una all&#39;altra utilizzando profili o strutture anatomiche 16-18. Registrazione sezioni istologiche seriali l&#39;un l&#39;altro senza l&#39;uso di immagini di riferimento può propagare errore di registrazione e cambiare la forma reale del volume istologia. Approccio registrazione Pair-saggio si basa sulla coerenza della forma delle sezioni istologici e le strutture interne per tutta la pila di immagini; quindi richiede denso campionamento del campione, chepotrebbe non sempre è possibile, ad esempio, per i campioni clinici. In questo gasdotto usiamo immagini blockface come un insieme di immagini di riferimento per il volume istologia ricostruzione 19. Blockface immagini sono prese dei blocchi di tessuto paraffina dopo il montaggio sul microtomo e prima di ogni sezione viene tagliata. Così, danni a individuo sezioni seriali taglio non interferisca con la registrazione di sezioni seriali 8,11,15. Catturiamo le immagini blockface in modo diverso dagli altri gruppi. Le immagini dei volti blocco ottico vengono raggiunti con un telecentrico per eliminare o minimizzare la canna e prospettiva distorsione, che di solito si verifica quando si utilizzano lenti regolari in ottica. Questo è uno dei vantaggi del metodo proposto rispetto agli altri metodi pubblicati, che eseguono l&#39;imaging blockface utilizzando lenti regolare. Le immagini sono riprese con una leggera angolazione obliqua di utilizzare la riflessione della superficie del blocco per migliorare il contrasto tra il TISSsuperficie ue e paraffina e di eliminare l&#39;ombra del tessuto in profondità sotto la superficie paraffina. Un filtro fotografico è anche usato per polarizzare la luce proveniente dalla superficie del blocco e il tessuto per bilanciare il contrasto 19. Per correggere lo spostamento del blocco sul microtomo rotativo da due a tre fori sono realizzati negli angoli del blocco, che sono facilmente rilevabili nelle immagini blockface. I centroidi di questi fori sono usati insieme con la registrazione rigida a base di riferimento-per allineare le immagini 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>
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		<tr height="21">
			<td height="21" style="height:21px;width:260px;">Leica EG 1160 Embedding Centre</td>
			<td style="width:179px;">Leica</td>
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			<td></td>
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		<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>
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		<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>
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reconstruction of 3-dimensional histology volume and its application to study mouse mammary glands

Ricostruzione del volume Istologia facilita lo studio della forma 3D e variazione di volume di un organo a livello di macrostrutture costituiti di cellule. Può anche essere usato per studiare e validare nuove tecniche e algoritmi di imaging medico volumetrico e terapie. Creazione di atlanti 3D ad alta risoluzione di diversi organi 1,2,3 è un&#39;altra applicazione di ricostruzione del volume istologia. Ciò fornisce una risorsa per indagare strutture tissutali e la relazione spaziale tra le varie funzioni cellulari. Vi presentiamo un metodo di registrazione di immagini per la ricostruzione del volume istologia, che utilizza una serie di immagini blockface ottiche. Il volume istologia ricostruito rappresenta una forma affidabile del campione trasformati senza propagate errore di registrazione post-processing. I ematossilina eosina (H &amp; E) sezioni colorate di due ghiandole mammarie topo sono stati registrati per le loro immagini blockface corrispondenti utilizzando punti di confine estratti dal ndrges del campione nelle immagini di istologia e blockface. La precisione della registrazione è stata valutata visivamente. L&#39;allineamento delle macrostrutture delle ghiandole mammarie stata anche valutata visivamente ad alta risoluzione. Questo studio delinea le diverse fasi di questa immagine registrazione conduttura, che vanno dalla escissione della ghiandola mammaria fino alla ricostruzione 3D del volume istologia. Mentre le immagini di istologia 2D rivelano le differenze strutturali tra coppie di sezioni, il volume istologia 3D offre la possibilità di visualizzare le differenze di forma e di volume delle ghiandole mammarie.

Un inconveniente di tradizionali tecniche di microscopia è che la comprensione di un organo a livello microscopico è limitata ad un campo di vista alla volta. Anche &quot;totale informative&quot; slides, che forniscono intere sezioni di scorrimento, non riescono a fornire informazioni tridimensionali. Con lo sviluppo di tutta la diapositiva, tecnologie di scansione dinamica, la nostra capacità di vedere una sezione nella sua interezza è aumentata, tuttavia estrapolando richiede strutture 3D ricostruzione del volume ...

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.

Ricostruzione di 3-Dimensional Volume Istologia e la sua applicazione per studiare mouse ghiandole mammarie

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.

Test di sensibilità visiva alla velocità e direzione del movimento in lucertole

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

Ricerca

Biologia

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.

Il ramo Ladder Walking attività: un sistema di punteggio e la sua applicazione pratica.

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.

Lens trapianto in Zebrafish e la sua applicazione nell&#39;analisi dei Mutanti Eye

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.

Topo cellule epiteliali mammarie forma Mammospheres durante la differenziazione lattogenica

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.

Valutazione dello Sviluppo ghiandola mammaria e funzione in modelli murini

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.

Iniezione intraduttale per Localizzato Drug Delivery per il mouse ghiandola mammaria

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.

High-throughput Immagine Analisi di sferoidi tumorali: Un software applicativo di facile utilizzo per misurare le dimensioni del Spheroids automaticamente e con precisione

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.

Utilizzando il mouse cellule tumorali mammarie per insegnare concetti di biologia di base: un modulo di laboratorio semplice

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.

Misurazione Loops Volume Pressione nel mouse

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