我们感谢安德烈亚斯·拉德布鲁赫的有价值的讨论。我们感谢萨宾Gruczek，帕特里克Thiemann和曼努埃拉Ohde援助与动物护理和罗伯特·冈瑟优秀的技术援助。我们感谢我们训练有素的评价者劳拉OEHME，Jannike巴亚特（Bayat） - Sarmadi，Karolin模特肖像权，卡特琳·罗斯，佛罗伦萨帕什和卡塔琳娜喇叭的组织学样品的评估和兰迪·林德奎斯特的手稿校对。我们感谢J.和N·李，梅奥诊所，斯科茨代尔，亚利桑那州，美国的MBP特异性抗体。 这项工作是支持的DFG HA5354 / 4-1，以JIMI - 一个用于活体显微镜DFG核设施网络补助和TRR130 / TP17和DFG FOR 2165（HA5354 / 6-1），以AEHSZ由国际马克斯·普朗克支持学校传染病和免疫（次展示-IDI），柏林。

动物实验批准动物福利（Landesamt献给GESUNDHEIT UND Soziales，柏林）适当的状态委员会，并按照现行准则和条例（动物实验许可G0194 / 11）进行。 1.产生荧光骨髓嵌合体小鼠注:荧光骨髓嵌合小鼠的产生可视化的骨髓基质细胞被作为9之前所述进行。 <ol><li>开始治疗德尔-酶Cre X ROSA-tdRFP小鼠（小鼠表达串联红色荧光蛋白（tdRFP）无所不在11-13）让他们做好准备的照射。另外，使用任何其他菌株荧光蛋白无处不体现。照射前两天施用新霉素经由饮水1毫克/毫升和1毫克/毫升的维生素（A，D3，E，C）。 </li><li>小鼠照射两次3.8灰色与铯-137伽玛辐照无线瘦3小时的间隔。对于此，将小鼠在适合于各自的照射的照射馅饼笼。 注:对于小鼠的辐射，我们的研究所不需要麻醉。按照有关麻醉照射本地机构的政策。如果有疼痛的迹象的照射后治疗的动物用5mg / kg每天卡洛芬皮下（SC）的。 </li><li>第二天，通过静脉内注射，从长骨的C57BL / 6供体小鼠中转移缓冲器9中制备3×10 6个骨髓细胞重建的小鼠。继续新霉素小鼠和维生素长达2周，在此期间，监测他们的幸福和重量。等待至少4周，以允许免疫系统的重建开始具体实验处理之前（ 例如 ，免疫）9。 </li><li>牺牲老鼠，并把它们放在夹层板，消毒腿用70％乙醇。 EuthanizË小鼠按照当地机构的政策。我们的研究所进行颈椎脱位。 </li><li>使用镊子和剪刀，从大腿取出皮肤。除去肌肉组织以暴露股骨。 Luxate从髋关节和膝关节使用镊子和剪刀的股骨。小心不要折断或切骨。 </li><li>小心地取出剩余的大块肌肉组织和软骨的使用剪刀骨。通过摩擦与实验室棉纸骨除去剩余的肌肉组织。收集的清洗骨头在培养皿用磷酸盐缓冲盐水（PBS）。 </li><li>整个修复股骨头骨在4％多聚甲醛（PFA，电子显微镜级）4 - 6小时。 </li><li>放弃PFA和孵化骨头在PBS O / N 10％的蔗糖。第二天，孵化的骨头20％的蔗糖O / N。后的第二天，孵化的骨头30％的蔗糖O / N。 </li></ol> 2. Cryosectioning骨骼注:1后，6 - 24小时，在30％的蔗糖，冷冻骨骼和根据川本的磁带方法14,15冷冻切片它们。 <ol><li>准备一个大烧杯（2000毫升体积）用干冰和丙酮（约2:1的体积比， 例如400毫升无水冰和200毫升丙酮的）下一个通风柜。放置一个小烧杯（150 - 250 ml，此）用己烷内（30 - 50毫升约）。等待混合降温（大约10分钟，直到霜出现在大烧杯中的外侧）。 </li><li>充满超级Cryoembedding中等（SCEM）标记cryomold的¾;小心地将里面挑骨头，直到他们完全沉浸，小心他们不接触模具的边缘。与大钳握住cryomold与刚好接触己烷的表面的模具底部的烧杯中。 <ol><li>让SCEM冻结的外边缘（由不透明度表明，这需要大约15秒）。然后完全放下模具放入正己烷和让它FRE结1 - 2分钟。取出冷冻的样品和包装玻璃纸，然后铝箔（以保护样品，从干燥并避免暴露于光）。储存在-80°C，直到cryosectioning。 </li></ol></li><li>股骨骨头cryosectioning使用标准的切片机切片机和刀片硬组织。 </li><li>设置切片的样品和叶片温度至-24℃。让切割前的切片机内的样品静置约15分钟。 <ol><li>固定样本块与SCEM或最佳切削温度（OCT）中的金属样品架。必要时可以调节该块的方向。修剪的样品，直到骨完全打开和骨髓是可见的。调整部分厚度为7μm（丢弃所述第一部分）。 </li><li>修复了一块川本磁带上使用鹿皮革覆盖的木制压舌板样品块顶部的粘性的一面。接着，切取试样，并打开带，使得该节定位在顶侧。磁带传送到使用镊子载玻片。固定胶带将载玻片用透明胶带。 </li></ol></li><li>让切片干燥至少30分钟，并且将它们存储在-80℃直至使用。存放在塑料载玻片盒与单个幻灯片之间间隔物未染色和未安装的滑动，以避免它们粘在一起。染色并安装幻灯片可以存储长达一个星期在纸板幻灯片文件夹中，在4℃。 </li></ol> 3.图片集<ol><li>按照常理免疫协议9解冻和染色冰冻切片。包括核染色剂， 例如，4&#39;，6二脒基-2-苯基吲哚二盐酸盐（DAPI）的可视化的组织的完整性。 注:色漆，例如用于RFP形象化基质细胞（抗RFP生物素抗体和链霉抗的Alexa Fluor 555），染色嗜酸性粒细胞与大鼠抗主要碱性蛋白（MBP）抗体和抗鼠的Alexa Fluor 647抗体细胞，B细胞用大鼠抗B220-的Alexa Fluor 594抗体和PC用抗κ轻链荧光素异硫氰酸酯（FITC）和抗λ1轻链FITC抗体（染色过程的细节在9中描述）。 </li><li>贴装染色切片:放一滴fluoromount的上部分，然后盖上＃1盖玻片，同时小心避免空气气泡的形成。接着，进行激光扫描共聚焦显微镜用装有适用于染色的激光线的工具。 </li><li>为了记录影像的骨髓造血细胞与使用Wimasis工具间质细胞，应用以下设置自动共定位分析: <ol><li>使用20X物镜和视的708.15 X 708.15微米的场。用于自动分析，保持在2048 X 2048像素（PX）相一致的所有图像的大小，以保持其结果媲美。 </li><li>记录一个通道的基质结构（ 例如， </em&gt; 561 nm激光线），对于核一个信道（ 例如，DAPI，405纳米）和附加信道为所关注的造血细胞（ 如，3路，488/594/633毫微米为嗜酸性粒细胞，B细胞和PC）。 </li><li>用行平均4月16日创纪录的图像。理想的情况下，覆盖整个股部分采取单相邻图像。可替代地，采取从骨髓（骨干以及骨骺）的各个区域不相邻的图片。 注意:要小心，不要产生相邻图像（以避免细胞重叠区域反复分析）之间的重叠。 </li></ol></li><li>将图像保存在显微镜的图像文件格式。检查和，如果需要的话，调整对比度在图像查看器/分析软件的所有通道。 </li><li>每幅图像的文件导出3 .jpg文件:用于DAPI通道（红/绿/蓝（RGB）格式，假彩色编码黄），用于信道间质1 .jpg文件（灰度）和一个.JPG 1 .jpg文件包含文件渠道造血细胞（最大3通道，RGB格式， 例如，FITC（电脑，假颜色:绿色）/的Alexa Fluor 594（B细胞，假的颜色:蓝色）/的Alexa Fluor 647（嗜酸性粒细胞，假的颜色:红色）） 。 </li></ol> 4.自动图像分析<ol><li>使用图像分析工具来执行图像分割，共定位和邻里的分析（见讨论 ）的量化。 </li><li>如果使用Wimasis工具，步骤如下: <ol><li>上传的每个图像3 .jpg文件集具有相同的文件名后加下划线和一个数字，表示图像的类型。 </li><li>使用_1与造血细胞.jpg文件，_2为的DAPI通道，_3为基质通道.jpg文件.jpg文件。例如:Image1_1.jpg（造血细胞），Image1_2.jpg（DAPI通道），并且Image1_3.jpg（基质信道）。通过客户帐户上传图片。 </li><li>对于细胞接触定量通过单击在相应字段中的细胞接触的工具。对于细胞附近的量化，选择单元附近工具，并进入在微米的优选半径附近（这是从该单元的边缘测量）。 </li><li>下载的结果。 注意:该结果被提供为.jpg文件表示的造血细胞，并与所检测的对象的边界的信道间质高​​亮，以及含有该测量对每个图像单一的.csv文件中，除了一个摘要.csv文件即包含所有上传的图片数据。 </li></ol></li><li>从接触测量确定与基质细胞，或红色，绿色，或蓝色的细胞接触的其他造血细胞类型的频率触点（造血细胞（红色，绿色，或蓝色的细胞）的示例中示出代表结果的频率， 图4）。为了确定频率，通过划分每个图像在给定接触计数每幅图像的总细胞计数。 <ol><li>用于与个体小鼠的实验中，总结了所有的图像的总接触计数为单个小鼠和由所有图像的总细胞计数的总和除以它们。 </li></ol></li><li>从附近的测量，确定如在步骤4.3（描述从基质细胞和/或红色，绿色或蓝色中的细胞优选接近其他造血细胞类型的频率的选择的距离内的红色，绿色或蓝色的细胞的频率也看到代表结果， 图4）。 </li></ol> 5.随机模拟骨髓的定位<ol><li>执行的随机细胞定位在模拟上所分析的骨髓组织学图像之前，预先准备了以下文件:由细胞接触工具机，原.jpg文件为DAPI通道和原始.jpg文件所提供的单个的.csv文件为基质的通道。 </li><li>为了进行在一系列图像批量模拟（ 例如，从一个股部分中的所有图像），收集在一个文件夹中的所有原始.jpg文件（_1，_2和_3）和相应的单的.csv文件。 注:模拟工具随机骨髓细胞定位可应要求提供。 </li><li>启动仿真工具，勾选"自动加载图像数据"。 注:该程序会自动读取.csv文件中的细胞计数及平均细胞大小。这些值显示在框"小区号"和"细胞大小AVG"（ 图5A）。 </li><li>输入常用的标签将.csv文件， 即在他们的名字的共同因素。输入应用于批处理模式模拟图像集的数目。 </li><li>加载从基质通道生成.jpg文件（文件名为结束_3）。 </li><li>输入用于产生从DAPI通道掩模设置: <ol><li>勾选"？申请掩模"为DAPI图像转换成二进制掩模10（ - 255范围0）设定阈值。 </li><li>勾选「8位？"勾选"扩张？"，并设置扩张的档次，以5像素。勾选「W /糜烂？"。 </li><li>输入的附近半径（邻域半径），用于模拟图像的分析所需的值。为708.15 X 708.15微米的大小为2048 X 2048像素的图像（像素缩放XY:0.346微米），29像素对应于10微米。 </li></ol></li><li>复选框"使用大津？"用大津算法17自动检测基质结构。 注意:这是一个用于通过接触和附近的工具相同的算法。在所记录的图像和模拟图像的自动分析使用相同的图像分割算法是至关重要的，以保持该数据具有可比性。 </li><li>输入设置为造血细胞，其中ArË模拟为圆形。 注:对于红，绿，和蓝单元的细胞数直接从.csv文件加载（也参见步骤5.6）。 <ol><li>使用仿真工具来计算红，绿和蓝单元的像素的平均直径。确定单个小区作为在图像中不同的细胞类型中像素由每幅图像的总细胞数除以该总面积的平均面​​积。使用的平均面积来计算使用下式的光盘的半径。一倍的半径来确定的平均直径。 </li></ol></li><li>测量所分析的细胞类型与任何图像分析软件，包括对象分割功能的细胞大小分布。确定σ为所有的造血细胞类型（18和图5B）。 注意:由于所记录的细胞的细胞大小分布不被自动图像分析测定，使用高斯分布作为真实分布的近似。吨的宽度他分布曲线由σ描述，并且可针对各种细胞类型完全不同。 （详情请参见图5B）。 <ol><li>从这些测量中，确定了"小区大小截止":描述仍确认为通过图像分析工具的完整细胞的最小对象像素的直径。 </li></ol></li><li>在图形用户界面（ 图5A）上的各框中输入参数。 <ol><li>进入细胞的大小切断， 即，在模拟允许的最小单元尺寸，如直径在像素。 </li><li>输入σ在像素为红色，绿色和蓝色的细胞（来自步骤5.9）中的细胞大小分布的模拟。 </li><li>检查小节"的面具细胞"中的"删除"复选框。通过此设置，程序就会选择一个新的位置为一个单元，如果它与至少一个像素与掩模的不走区域重叠。勾选「避免细胞重叠？̶1;在小节"细胞排斥"。 </li><li>输入两个细胞在像素的中心之间所允许的最小距离。 注:最小距离需要从所记录的图像来确定。错误地测量最小距离会导致偏见/人工结果记录和模拟图像的对比。 </li><li>重叠的最大面积设定为100％，如果该重叠是由最小距离从中心定义为中心。 </li><li>设置模拟工具1000重复。 </li><li>勾选"自动保存细胞？"保存模拟对象的坐标批为.rect文件（文本格式）的每个图像的所有重复。勾选"自动保存图像？"保存.TIFF文件中为每个模拟图像。输入一个共同的标签保存的文件。 注:"？自动保存细胞"选项可减少模拟运行时间和整体数据的大小，节省了比较实际的模拟IMA时GES。所述.rect文件模拟细胞的坐标保存为矩形，如果需要，可因此被转换成模拟图像。 </li></ol></li><li>通过点击"运行模拟"开始模拟。 注:仿真工具自动生成.csv文件为1000模拟每个图像，其中包括平均接触计数和附近计数为红，绿和蓝单元以红，绿，蓝，和间质细胞的每个组重复模拟。此外，对于所有的这些值，被设置在1000模拟与标准偏差（STD）和平均值的标准误差（SEM）的平均值。 </li><li>确定平均接触频率和一组1,000个模拟图像附近的频率。为此，除以每幅图像的记录细胞计数的平均接触及周边地区计数。比较的频率，以所记录的图像的自动的共定位分析的结果。 </li><li>应用适当的为static根据分析19 stical方法（ 图7中 ，我们使用了双尾Wilcoxon符号秩检验）。 </li></ol>

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Juan Escribano Navarro is affiliated with Wimasis GmbH, Munich, Germany. The other authors have no conflicts of interest to declare.

尽管在现代光学成像方法的进步，组织学数据的分析仍经常因缺乏适当的量化工具和方法，或偏颇的分析，重点关注小面积的阻碍。这里介绍的协同方法结合图像分析覆盖整个骨髓区域，自动分割和识别物体的各种造血和间质细胞类型，共定位分析，并通过了新的定做提供的非随机发生的接触最终验证工具设计仿真软件。 整个骨骼包括骨髓组织学一直难以进行，由于各种组?...

由于在显微镜最近快速的技术发展，包括光学成像，整个组织的范围内的细胞的分析已成为免疫学家越来越容易获得。单细胞的悬浮液的表征代表有价值的，不可缺少的方法来了解细胞和分子的功能。然而，该细胞的内它们的（微）-anatomical环境分析对于理解在复杂过程互相协作，如免疫反应的发展各种细胞类型之间的相互作用是必不可少的。 虽然这是相对容易的显微镜，以获得从图像质量信息，但它仍然量化这些数据是一个挑战，部分原因是由于在这个领域的分析方法进行滞后相比，现在有可能在图像采集的事实。许多研究人员仍然依靠耗时在他们的组织学图像手动细胞计数，从而带来了一种偏见之间不同的评价者和其他团体阻碍复制。通常情况下，一个代表图像被选择为强调对细胞的位置或共定位的声明在一个出版物，难以为读者来判断这样的事件的统计相关性。 再加上事实，即图像数据的全部信息内容很少利用，这强调了需要一个更公正，更快速和全面的方法来分析组织的图像。 骨髓是一个复杂的组织，这需要对重要生命功能作为造血在成年脊椎动物的器官。除了 ​​是发源地为造血细胞1,2和打在B淋巴细胞发育3中起重要作用，它也可以作为一个网站，免疫反应引发4和支持成熟，再循环的B细胞5。此外，其在维持我的作用mmunological存储器已经越来越意识到，在过去的十年中，作为多种类型构成免疫记忆细胞已被发现位于那里6-9。 骨髓复杂的组织结构和功能之间的关系仍然难以捉摸。不同于次级淋巴器官，这些组织在宏观室如T和B细胞区，骨髓缺乏明确宏观条块。到目前为止鲜明隔间骨髓由其邻近骨皮质或脉管限定。在骨髓中的多个进程的各个驻地基质细胞群如支持干细胞，B细胞或维护免疫记忆细胞群（如长寿命的浆细胞（PC机），CD4 +和发育的重要性CD8 +记忆T细胞）清楚地表明，存在一定程度的微区室中的骨髓。 <p类="jove_content"&gt;这些观察导致了不同的显微解剖龛，这是专门在某些功能（干细胞维持，B细胞发育的各个阶段，和维护的免疫记忆）在骨髓中的概念。尽管似乎有一定程度的异质性的服务于不同功能的壁龛中，一些由基质细胞，如CXC趋化因子配体12（CXCL12）或白介素-7（IL-7），所产生的因素是非常重要的组件这几条龛10。在骨髓中的可视化和基质细胞的表征是困难的，因为它们与长而细的树突延伸形成整个骨髓的网络的形态特征，并且缺乏适当的标记，以辨别基质亚群。 目前尚不清楚在何种程度上这些利基相对于它们的细胞和分子构成因素的共同特点n和哪些元素呈现一定的利基独特。除了基质细胞，造血细胞类型已经显示通过提供某些信号的至少一段的壁龛中发挥关键作用。显然，小生组合物的复杂性，需要他们的原位分析，它已成为日益重要的免疫学家和血液科放大对骨髓微， 例如，通过分析其细胞成分之间的空间关系。 这里，一个策略来量化在骨髓中的自动化和无偏方式蜂窝共定位和邻里关系呈现。详细的工作流程，包括嵌合小鼠的产生，窝藏荧光基质细胞和非荧光的造血细胞，制备从脱钙骨，采集覆盖整个骨的共焦图象的组织切片，以及蜂窝C的自动图像分析邻定位及验证/从随机定位由一个模拟工具判别被设置（ 图8）。

<table><tbody><tr><td>Neomycin</td><td><a href="http://www.sigmaaldrich.com" target="_blank"><img src="/img/new_window.png" /> Sigma</a></td><td>N6386 SIGMA</td><td>Neomycin trisulfate salt hydrate, EU hazard code: GHS08</td></tr><tr><td>Ursovit AD3EC</td><td>Serumwerke Bernburg</td><td></td><td>1 ml contains: 50.000 I.E. retinyl palmitate, 5.000 I.E. cholecalciferol, 30 mg tocopheryl acetate, 100 mg ascorbic acid, 1 mg sorbic acid, 200 mg polyoxyl 35 castor oil, 0,5 mg propyl gallate</td></tr><tr><td>Transfer buffer (100 ml PBS, 1 ml 1 M HEPES, 50 U/ml penicillin/streptomycin)</td><td><a href="http://www.sigmaaldrich.com" target="_blank"><img src="/img/new_window.png" /> Sigma</a></td><td>P4333, H3375</td><td></td></tr><tr><td>4-Hydroxy-3-nitrophenylacetyl hapten conjugated to chicken gamma globulin</td><td></td><td></td><td></td></tr><tr><td>Chicken gamma globulin (CGG) 100 mg</td><td><a href="http://www.rockland-inc.com" target="_blank"><img src="/img/new_window.png" /> Rockland</a></td><td>D602-0100</td><td></td></tr><tr><td>20% Paraformaldehyde solution (EM-grade)</td><td>Science Services</td><td>15713</td><td>EU hazard codes: GHS02, GHS05, GHS07, GHS08</td></tr><tr><td>D(+)-sucrose</td><td><a href="http://www.carlroth.com" target="_blank"><img src="/img/new_window.png" /> Carl Roth</a></td><td>4621.1</td><td></td></tr><tr><td>Dry ice</td><td></td><td></td><td></td></tr><tr><td>Acetone</td><td><a href="http://www.sigmaaldrich.com" target="_blank"><img src="/img/new_window.png" /> Sigma-Aldrich</a></td><td>179124 SIGMA-ALDRICH</td><td>EU hazard codes: GHS02, GHS07</td></tr><tr><td>Hexane</td><td><a href="http://www.sigmaaldrich.com" target="_blank"><img src="/img/new_window.png" /> Sigma-Aldrich</a></td><td>208752 SIGMA-ALDRICH</td><td>EU hazard codes: GHS02, GHS07, GHS08, GHS09</td></tr><tr><td>Tissue-Tek cryomolds (standard)</td><td><a href="http://www.sakuraus.com" target="_blank"><img src="/img/new_window.png" /> Sakura</a></td><td>4557</td><td>25 x 20 x 5 mm</td></tr><tr><td>Tissue-Tek O.C.T.</td><td><a href="http://www.sakuraus.com" target="_blank"><img src="/img/new_window.png" /> Sakura</a></td><td>4583</td><td></td></tr><tr><td>Kawamoto&#039;s SCEM embedding medium</td><td><a href="http://section-lab.jp/index.html" target="_blank"><img src="/img/new_window.png" /> Section-Lab, JP</a></td><td></td><td></td></tr><tr><td>Kawamoto&#039;s cryosection preparation kit&amp;nbsp;</td><td><a href="http://section-lab.jp/index.html" target="_blank"><img src="/img/new_window.png" /> Section-Lab, JP</a></td><td></td><td></td></tr><tr><td>Kawamoto&#039;s cryofilm type 2C(9)</td><td><a href="http://section-lab.jp/index.html" target="_blank"><img src="/img/new_window.png" /> Section-Lab, JP</a></td><td></td><td></td></tr><tr><td>Microtome blade MX35 premier plus, low profile</td><td><a href="http://www.thermoscientific.com" target="_blank"><img src="/img/new_window.png" /> Thermo Scientific</a></td><td>3052835</td><td>L X W: 80 x 8 mm (31.5 x 3.13&quot;), thickness: 0.25 mm (0.01&quot;)</td></tr><tr><td>Polyclonal rabbit anti-RFP antibody, biotinylated</td><td><a href="http://www.rockland-inc.com" target="_blank"><img src="/img/new_window.png" /> Rockland</a></td><td>600-406-379</td><td></td></tr><tr><td>Alexa Fluor 555 streptavidin</td><td><a href="http://www.lifetechnologies.com" target="_blank"><img src="/img/new_window.png" /> Life Technologies</a></td><td>S-32355</td><td></td></tr><tr><td>Rat anti-MBP</td><td>J. and N. Lee</td><td></td><td>available from: J. and N. Lee, Mayo Clinic, Scottsdale, AZ , U.S.A., clone MT-14.7</td></tr><tr><td>Goat anti-rat-Alexa Fluor 647</td><td><a href="http://www.lifetechnologies.com" target="_blank"><img src="/img/new_window.png" /> Life Technologies</a></td><td>A-21247</td><td></td></tr><tr><td>Rat anti-B220 - Alexa Fluor 594</td><td></td><td></td><td>produced and coupled in-house (DRFZ), clone RA3.6B2, Alexa Fluor 594 from Life Technologies</td></tr><tr><td>Mouse anti-l1 light chain -FITC</td><td></td><td></td><td>produced and coupled in-house (DRFZ), clone LS136</td></tr><tr><td>Rat anti-k light chain - FITC</td><td></td><td></td><td>produced and coupled in-house (DRFZ), clone 187.1</td></tr><tr><td>DAPI (4&amp;prime;,6-diamidino-2-phenylindole dihydrochloride)</td><td><a href="http://www.sigmaaldrich.com" target="_blank"><img src="/img/new_window.png" /> Sigma</a></td><td>D9542 SIGMA</td><td></td></tr><tr><td>Fluorescent mounting medium</td><td><a href="http://www.dako.com" target="_blank"><img src="/img/new_window.png" /> DAKO</a></td><td>S3023</td><td></td></tr><tr><td>Cover slips (24 x 24 x 0.13-0.16 mm)</td><td><a href="http://www.carlroth.com" target="_blank"><img src="/img/new_window.png" /> Carl Roth</a></td><td>H875.2</td><td></td></tr><tr><td>Superfrost slides glasses (75 x 25 mm)</td><td><a href="http://www.vwr.com" target="_blank"><img src="/img/new_window.png" /> VWR</a></td><td>48311-703</td><td></td></tr><tr><td>Laser scanning confocal microscope</td><td></td><td></td><td>equipped with laser lines of 405, 488, 561, 594, 633 nm and a 20X/0.8 NA air objective lens. We used a Zeiss LSM710 and Zen 2010 Version 6.0 software.</td></tr><tr><td>Automated image analysis tools for bone marrow</td><td><a href="http://www.wimasis.de" target="_blank"><img src="/img/new_window.png" /> Wimasis, Munich</a></td><td></td><td>The cell contact tool and cell vicinity tool will be made available by Wimasis upon request.</td></tr><tr><td>VC2012 runtime</td><td>Microsoft</td><td></td><td>&lt;a href=&quot;http://www.microsoft.com/en-us/download/details.aspx?id=30679&quot; target=&quot;_blank&quot;&gt;free download&lt;/a&gt;</td></tr><tr><td>Simulation tool for random cell positioning</td><td></td><td></td><td>available from us, upon request</td></tr><tr><td>Image analysis software with image segmentation functions</td><td></td><td></td><td>We used Volocity (Perkin Elmer) for measuring cell size distributions of hematopoietic cell types in bone marrow (&lt;strong&gt;Figure 5&lt;/strong&gt;). Alternatives are Definiens Image Analysis (Definiens) or Cell Profiler (&lt;a href=&quot;http://www.cellprofiler.org&quot; target=&quot;_blank&quot;&gt;free download&lt;/a&gt;)</td></tr><tr><td>Fiji image analysis software&amp;nbsp;</td><td></td><td></td><td>&lt;a href=&quot;http://fiji.sc/Fiji&quot; target=&quot;_blank&quot;&gt;free download&lt;/a&gt;. Fiji was used by trained raters for manual cell count (&lt;strong&gt;Figure 3&lt;/strong&gt;).</td></tr></tbody></table>

automated quantification of hematopoietic cell &#8211; stromal cell interactions in histological images of undecalcified bone

共聚焦显微镜是用于复杂的组织中的多个细胞类型中的定位的分析选择的方法，如骨髓。然而，细胞定位的分析和定量是困难的，因为在许多情况下，它依赖于人工计数，从而轴承引入评价者依赖性偏差和减少间信的风险。此外，它往往是难以判断是否之间从随机定位两个小区的结果的共定位，特别是当细胞类型在它们发生的频率强烈不同。这里，用于蜂窝共定位于骨髓的无偏量化的方法被引入。该协议描述了用于获得全鼠长骨的组织切片，包括骨髓样品制备，以及在染色方案和获得高清晰度图像。分析工作流程从识别造血和非HEMAT的跨越在2维（2D）的骨髓的图像的那些细胞之间的直接接触的量化opoietic细胞类型呈现。这还包括一个邻域分析，以获得关于周围某一细胞类型的细胞微环境的信息。为了评价共定位两种细胞类型是否是随机的细胞定位的光效或反映了细胞间优先关联，一个模拟的工具，它适用于测试这个假设在造血以及基质细胞的情况下，是使用。这种方法不限定于骨髓，并可以扩展到其他组织中，以允许组织学数据的重现性好，定量分析。

切割脱钙骨的冷冻切片与川本磁带方法允许整个骨进行切割作为一个完整的部分，与仍连接到矿化骨内膜区域的骨髓，无论是在骨干以及与骨骺区域其高密度骨小梁（ 图1）。各部分的核染色显示，尽管在制备小裂缝不能完全避免，该正弦和动脉的结构，以及实质的网状网络保持不变。 作为红色荧光嵌合骨髓的免疫荧光染色的一个例子，它的随后的分析中，示出?...

Watch this Scientific Journal Video about Automated Quantification of Hematopoietic Cell Ã¢â‚¬â€œ Stromal Cell Interactions in Histological Images of Undecalcified Bone at JoVE.com

Automated Quantification of Hematopoietic Cell &#8211; Stromal Cell Interactions in Histological Images of Undecalcified Bone

A strategy to quantitatively analyze histological data in the bone marrow is presented. Confocal microscopy of fluorescently labeled cells in tissue sections results in 2-dimensional images, which are automatically analyzed. Co-localization analyses of different cell types are compared to data from simulated images, giving quantitative information about cellular interactions.

造血干细胞的自动定量 - 在脱钙骨的组织学图像间质细胞的相互作用

Confocal microscopy is the method of choice for the analysis of localization of multiple cell types within complex tissues such as the bone marrow. ...

automated-quantification-hematopoietic-cell-stromal-cell-interactions

Research

JoVE Journal

Developmental Biology

11.5K 次观看.  German Rheumatism Research Center, a Leibniz Institute. A strategy to quantitatively analyze histological data in the bone marrow is presented. Confocal microscopy of fluorescently labeled cells in tissue sections results in 2-dimensional images, which are automatically analyzed. Co-localization analyses of different cell types are compared to data from simulated images, giving quantitative information about cellular interactions.

视频: Automated Quantification of Hematopoietic Cell – Stromal Cell Interactions in Histological Images of Undecalcified Bone

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

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

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

利用卡尔瓦里亚共同培养和教条法测量骨重塑和再造肿瘤-骨微环境

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

科研

癌症研究

Discovery of Metastatic Regulators using a Rapid and Quantitative Intravital Chick Chorioallantoic Membrane Model

Recent advances in cancer research has illustrated the highly complex nature of cancer metastasis. Multiple genes or genes networks have been found to be involved in differentially regulating cancer metastatic cascade genes and gene products dependent on the cancer type, tissue, and individual patient characteristics. These represent potentially important targets for genetic therapeutics and personalized medicine approaches. The development of rapid screening platforms is essential for the identification of these genetic targets.
The chick chorioallantoic membrane (CAM) is a highly vascularized, collagen rich membrane located under the eggshell that allows for gas exchange in the developing embryo. Due to the location and vascularization of the CAM, we developed it as an intravital human cancer metastasis model that allows for robust human cancer cell xenografting and real-time imaging of cancer cell interactions with the collagen rich matrix and vasculature. 
Using this model, a quantitative screening platform was designed for the identification of novel drivers or suppressors of cancer metastasis. We transduced a pool of head and neck HEp3 cancer cells with a complete human genome shRNA gene library, then injected the cells, at low density, into the CAM vasculature. The cells proliferated and formed single-tumor cell colonies. Individual colonies that were unable to invade into the CAM tissue were visible as a compact colony phenotype and excised for identification of the transduced shRNA present in the cells. Images of individual colonies were evaluated for their invasiveness. Multiple rounds of selections were performed to decreases the rate of false positives. Individual, isolated cancer cell clones or newly engineered clones that express genes of interest were subjected to primary tumor formation assay or cancer cell vasculature co-option analysis. In summary we present a rapid screening platform that allows for anti-metastatic target identification and intravital analysis of a dynamic and complex cascade of events.

This is an effective method to screen for suppressors or drivers of cancer metastasis. Cells, transduced with an expression library, are injected into the chicken chorioallantoic membrane vasculature to form metastatic colonies. Colonies having decreased or increased invasiveness are excised, expanded, reinjected to confirm their phenotype, and finally, analyzed using high throughput sequencing.

使用快速和定量的细胞内胆碱膜模型发现转移调节器

Recent advances in cancer research has illustrated the highly complex nature of cancer metastasis. Multiple genes or genes networks have been found to be ...

Undecalcified Bone Preparation for Histology, Histomorphometry and Fluorochrome Analysis

Undecalcified bone histology demonstrates the micro-architecture of bone. It shows both the mineralised and cellular components of bone, which provides vital information on bone turnover or bone formation and resorption. This has tremendous importance in a variety of clinical and research applications. It yields beautiful images1 and allows for techniques such as fluorochrome assessment and histomorphometry2. Fluorochrome analysis is a technique where fluorescent dyes that bind to calcium are injected at a particular time point, which allows for quantification of the amount of mineralisation at that given time. Histomorphometry is a process of bone quantification at the microscopic level. 
Performing undecalcified bone histology is technically challenging, particularly with large size specimens. It requires variations in technique from those used in standard paraffin embedded histology. This video illustrates the process of producing good quality sections and demonstrates the technical difficulties and methods with which to overcome them. Specimen preparation, fixation and processing are achieved with a manner similar to other soft tissues, however due to the density and lower permeability of bone considerably longer fixation and processing times are required, often taking several weeks. Embedding is achieved using a supporting medium with similar or equal hardness and density to the bone such as methacrylate- based resins, but unlike paraffin infiltration and embedding, this is an irreversible step. Sectioning can be achieved by grinding which produces a thicker section, which is optimal for studies such as fluorochrome analysis. This is best achieved using a diamond blade on a macrotome. Alternatively, thinner sections can be produced for light microscopy and this is achieved using a sledge microtome with a very sharp blade. The sledge microtome provides the additional strength and stability required for large, hard blocks. Resin embedded sections can be stained with a variety of stains, which are demonstrated.

Undecalcified bone histology provides important information for a variety of clinical and research applications. It is technically challenging, particularly with large size specimens. This video illustrates the process of producing good quality sections and demonstrates the technical difficulties and methods with which to overcome them.

脱钙骨组织学，形态计量学和荧光染料分析制备

Undecalcified bone histology demonstrates the micro-architecture of bone. It shows both the mineralised and cellular components of bone, which provides ...

生物学

A Semi-Automated and Reproducible Biological-Based Method to Quantify Calcium Deposition In Vitro

Vascular calcification involves a series of degenerative pathologies, including inflammation, changes to cellular phenotype, cell death, and the absence of calcification inhibitors, that concomitantly lead to a loss of vessel elasticity and function. Vascular calcification is an important contributor to morbidity and mortality in many pathologies, including chronic kidney disease, diabetes mellitus, and atherosclerosis. Current research models to study vascular calcification are limited and are only viable at the late stages of calcification development in vivo. In vitro tools for studying vascular calcification use end-point measurements, increasing the demands on biological material and risking the introduction of variability to research studies. We demonstrate the application of a novel fluorescently labeled probe that binds to in vitro calcification development on human vascular smooth muscle cells and determines the real-time development of in vitro calcification. In this protocol, we describe the application of our newly developed calcification assay, a novel tool in disease modeling that has potential translational applications. We envisage this assay to be relevant in a broader spectrum of mineral deposition research, including applications in bone, cartilage, or dental research.

A Semi-Automated and Reproducible Biological-Based Method to Quantify Calcium Deposition In Vitro

Cardiovascular disease is the leading cause of death worldwide. Vascular calcification contributes substantially to the burden of cardiovascular morbidity and mortality. This protocol describes a simple method to quantify vascular smooth muscle cell-mediated calcium precipitation in vitro by fluorescent imaging.

一种半自动且可重现的基于生物学的体外定量钙沉积的方法

Vascular calcification involves a series of degenerative pathologies, including inflammation, changes to cellular phenotype, cell death, and the absence ...

生物化学

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

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

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

用 Imagej 插件对小梁骨的外边界辅助分割和量化

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

生物工程

Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures

Quantification of cells is necessary for a wide range of biological and biochemical studies. Conventional image analysis of cells typically employs either fluorescence detection approaches, such as immunofluorescent staining or transfection with fluorescent proteins or edge detection techniques, which are often error-prone due to noise and other non-idealities in the image background. 
We designed a new algorithm that could accurately count and distinguish macrophages and fibroblasts, cells of different phenotypes that often colocalize during tissue regeneration. MATLAB was used to implement the algorithm, which differentiated distinct cell types based on differences in height from the background. A primary algorithm was developed using an area-based method to account for variations in cell size/structure and high-density seeding conditions. 
Non-idealities in cell structures were accounted for with a secondary, iterative algorithm utilizing internal parameters such as cell coverage computed using experimental data for a given cell type. Finally, an analysis of coculture environments was carried out using an isolation algorithm in which various cell types were selectively excluded based on the evaluation of relative height differences within the image. This approach was found to accurately count cells within a 5% error margin for monocultured cells and within a 10% error margin for cocultured cells.

We present a method, which utilizes a generalizable area-based image analysis approach to identify cell counts. Analysis of different cell populations exploited the significant cell height and structure differences between distinct cell types within an adaptive algorithm.

基于面积的图像分析算法，用于巨噬细胞-成纤维细胞共生群的定量

Quantification of cells is necessary for a wide range of biological and biochemical studies. Conventional image analysis of cells typically employs either ...

In Vivo 4-Dimensional Tracking of Hematopoietic Stem and Progenitor Cells in Adult Mouse Calvarial Bone Marrow

Through a delicate balance between quiescence and proliferation, self renewal and production of differentiated progeny, hematopoietic stem cells (HSCs) maintain the turnover of all mature blood cell lineages. The coordination of the complex signals leading to specific HSC fates relies upon the interaction between HSCs and the intricate bone marrow microenvironment, which is still poorly understood[1-2].
We describe how by combining a newly developed specimen holder for stable animal positioning with multi-step confocal and two-photon in vivo imaging techniques, it is possible to obtain high-resolution 3D stacks containing HSPCs and their surrounding niches and to monitor them over time through multi-point time-lapse imaging. High definition imaging allows detecting ex vivo labeled hematopoietic stem and progenitor cells (HSPCs) residing within the bone marrow. Moreover, multi-point time-lapse 3D imaging, obtained with faster acquisition settings, provides accurate information about HSPC movement and the reciprocal interactions between HSPCs and stroma cells.
Tracking of HSPCs in relation to GFP positive osteoblastic cells is shown as an exemplary application of this method. This technique can be utilized to track any appropriately labeled hematopoietic or stromal cell of interest within the mouse calvarium bone marrow space.

In Vivo 4-Dimensional Tracking of Hematopoietic Stem and Progenitor Cells in Adult Mouse Calvarial Bone Marrow

The nature of the interactions between hematopoietic stem and progenitor cells (HSPCs) and bone marrow niches is poorly understood. Custom hardware modifications and a multi-step acquisition protocol allow the use of two-photon and confocal microscopy to image ex vivo labeled HSPCs homed within bone marrow areas, tracking interactions and movement.

在造血干细胞和祖细胞的成年小鼠颅骨骨髓体内四维跟踪

Through a delicate balance between quiescence and proliferation, self renewal and production of differentiated progeny, hematopoietic stem cells (HSCs) ...

优化从胸腺和骨髓中分离基质细胞

Stromal Cell Isolation From Hematopoietic Organs

Single-cell sequencing has enabled the mapping of heterogeneous cell populations in the stroma of hematopoietic organs. These methodologies provide a lens through which to study previously unresolved heterogeneity at steady state, as well as changes in cell type representation induced by extrinsic stresses or during aging. Here, we present step-wise protocols for the isolation of high-quality stromal cell populations from murine and human thymus, as well as murine bone and bone marrow. Cells isolated through these protocols are suitable for generating high-quality single-cell multiomics datasets. The impacts of sample digestion, hematopoietic lineage depletion, FACS analysis/sorting, and how these factors influence compatibility with single-cell sequencing are discussed here. With examples of FACS profiles indicating successful and inefficient dissociation and downstream stromal cell yields in post-sequencing analysis, recognizable pointers for users are provided. Considering the specific requirements of stromal cells is crucial for acquiring high-quality and reproducible results that can advance knowledge in the field.

作者聚焦：使用基质细胞分离进行单细胞测序推进造血研究

Here we present protocols that enable isolation of stromal cells from murine bone, bone marrow, thymus and human thymic tissue compatible with single-cell multiomics.

从造血器官中分离基质细胞

Single-cell sequencing has enabled the mapping of heterogeneous cell populations in the stroma of hematopoietic organs. These methodologies provide a lens ...

造血干细胞的自动定量 - 在脱钙骨的组织学图像间质细胞的相互作用

摘要

探索更多视频

利用卡尔瓦里亚共同培养和教条法测量骨重塑和再造肿瘤-骨微环境

使用快速和定量的细胞内胆碱膜模型发现转移调节器

脱钙骨组织学，形态计量学和荧光染料分析制备

一种半自动且可重现的基于生物学的体外定量钙沉积的方法

用 Imagej 插件对小梁骨的外边界辅助分割和量化

基于面积的图像分析算法，用于巨噬细胞-成纤维细胞共生群的定量

在造血干细胞和祖细胞的成年小鼠颅骨骨髓体内四维跟踪

从造血器官中分离基质细胞

从造血器官中分离基质细胞

从造血器官中分离基质细胞