我们感谢 Hotchkiss 脑研究所高级显微镜平台提供的成像基础设施和专业知识。RWJ 得到了卡尔加里大学 Eyes High 计划的博士后奖学金资助以及加拿大多发性硬化症协会和加拿大罗氏无限制教育奖学金的支持。VWY 获得了加拿大研究主席 Tier 1 计划的薪资支持。这项工作得到了加拿大卫生研究院研究资助 1049959、加拿大多发性硬化症协会资助 3236 和美国国防部国会指导的多发性硬化症研究计划的运营资金的支持。 图 1 是使用 BioRender.com 创建的。本出版物中改编的数字最初发表在 The Journal of Immunology 上。Rajiv W. Jain、David A. Elliott 和 V. Wee Yong。2023. 使用 Histoflow Cytometry 对高参数组织学图像进行单细胞分析。 免疫学杂志。210: 2038-2049.版权所有 © [2023]。美国免疫学家协会

用于高参数组织成像的免疫荧光显微镜检查和分析

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这里描述了组织流式细胞术的使用，这种技术之前已经验证了18.结果表明，当使用光谱重叠染料对组织切片进行染色时，可以使用光谱补偿去除跨通道的渗漏，从而比通常通过传统方法清晰分辨更多的荧光参数。由于使用传统方法难以分析高参数组织学图像，因此提供了一个分析管道来从这些图像中分割单个细胞。通过导出这些单个细胞的荧光特征，证明像在流式细胞术中进行的单细胞分析同样可以应用于组织学图像。虽然流式细胞术不包括空间分析，但研究表明，组织流式细胞术可以将通过设门策略鉴定的群体映射回组织切片上，以评估其空间定位。总体而言，证明组织流式细胞术结合了流式细胞术和组织学的优势。
虽然组织流式细胞术具有保留空间信息的优势，但它也具有许多与传统组织学相同的局限性。虽然流式细胞术非常适合量化整个组织中的细胞，但组织学通常是通过分析具有组织代表性的一小部分组织切片样本来进行的。为了使组织学准确量化组织中的细胞数量，需要对从组织中提取的每个组织切片进行成像，并量化每个切片中的细胞数量，这是不切实际的。另一个问题是，在组织切片过程中，一些细胞会一分为二，并且无法重建这些细胞。事实上，此处列出的方案的一个局限性是它不包括任何排除组织边缘细胞的方法。尽管存在这些限制，但与流式细胞术相比，组织流式细胞术的一个优势是无需将组织解离成单细胞悬液，这可能会给分离或捕获不充分的细胞群带来偏差22。因此，虽然组织流式细胞术与传统流式细胞术相比具有多项优势，但获得整个组织的测量结果仍将是一个挑战。
在这里，证明了可以分离八个光谱重叠的荧光参数;然而，其他人已经成功分离了 13 种荧光染料17。可分离的染料数量取决于收集数据的显微镜的特性。荧光染料的最佳激发波长和最常见的发射波长不同。利用这些特性的显微镜通过使用宽范围的激发波长来更精确地匹配荧光基团的最佳激发波长，并通过调整发射检测器来精确匹配最频繁的发射波长，这将最大限度地分离荧光染料。最大限度地减少光谱重叠对于生成高质量数据至关重要，因为补偿跨通道的渗漏可能会影响荧光团彼此相互作用的检测动态范围，因此，基于发射和激发的分离是分离荧光团的关键第一步。根据显微镜的特性和需要成像的荧光参数的数量，可能需要将具有相同激发波长但发射波长不同的多个荧光团放在相同的激光线上。这通常是通过将基础荧光染料与偶联荧光染料结合使用来实现的，其中偶联染料以更长的波长发射，因此可以根据它们的发射波长进行区分。总体而言，必须通过激发或发射频率来区分染料，才能有效分离。
获得完美补偿因多种因素而变得复杂，包括补偿的空间方面。首先，荧光团是否发射光子部分基于机会23，其中每个图像中收集的光子都偏向于致密染色的位置。但是，染色密度较低的区域可能会偶然发射一个光子，该光子出现在其中一个重叠通道中，但不出现在主通道中。由于补偿是基于每个体素应用的，因此由于缺乏空间共定位，因此在补偿期间不会消除光谱重叠。这可以在图 2 中看到，其中补偿导致致密染色的位置（微珠的边缘）减少，但微珠的中心没有减少，那里的染色最小，与渗出通道的重叠较差。微珠中心的这种染色可能是由于另一个可能影响补偿的问题，即在焦平面外产生的光子可能会出现在焦平面中的体素中，这些体素不太可能在主通道和需要补偿的通道中再现24。因此，如果不引入过度补偿，这种“噪声”将无法通过补偿有效消除。通过使用线平均值、多次测量单个体素的荧光值以及使用平均值来限制随机机会事件的影响，可以部分地解决这些问题。如果使用共聚焦显微镜，也可以减小针孔尺寸，以排除离焦光子被纳入图像中25,26。使用这些修复的代价是额外的成像采集时间，这可能会变得很长。
虽然这项技术是使用共聚焦显微镜拍摄的图像开发的，但它也适用于其他类型的显微镜。其他使用类似方法的人将这些方法应用于从双光子显微镜拍摄的图像17 并取得了巨大成功。虽然这项技术可以应用于从宽场显微镜拍摄的图像，但共聚焦显微镜有几个优点，可以提高分辨光子是否起源于焦平面内。由于光子位置的精确分辨率（即光学切片）提高了补偿质量，因此预计补偿质量会相对较差。这可以通过使用反卷积去除离焦光子来提高宽场图像的分辨率来解决27。确定反卷积是否与该协议兼容的一个重要警告是，每个通道中的荧光值在所有分析的图像中是否保持彼此成比例。如果反卷积后的荧光值变得任意，那么在一个图像上生成的相同补偿矩阵不太可能成功应用于其他图像。总的来说，决定显微镜是否可以使用此工作流程的最重要因素是该显微镜是否具有可以灵活调整检测范围的探测器。如果这是可用的，那么可以通过在不同检测窗口内检测它们的发射光谱来解析通过相同激发激发的多个荧光团。
如果与对同一组织进行多次连续染色的技术相结合13，例如 IBEX14,15，荧光参数的数量可以进一步增加。使用连续染色，可以有效地测量无限数量的参数;但是，这可能非常耗时。将此处讨论的补偿方法与连续染色结合使用可以大大减少拍摄这些图像所需的时间，因为每轮染色可以同时对更多通道进行成像。此处描述的分析管道将根据需要扩展任意数量的标记物，并与连续染色的组织切片兼容。
该分析流程中的一个关键步骤是从组织学图像中分割单个细胞。寻找有效的策略从组织学图像中准确分割细胞是一个常见问题28，并且正在不断开发新的方法。虽然这种方法可以有效地将单个细胞与紧密排列的细胞分开，但细胞的确切边界往往并不完美。因此，建议用户将分析仅限于他们感兴趣的细胞群，因为需要分离的细胞越少，细胞边界就越准确。用户还可以通过在 ilastik 中定义多个细胞群来实现更好的细胞分离，从而允许程序分割出不同的细胞群。然而，这种方法的一个问题是，以这种方式定义的单元格不能在软件 3 中合并到同一个“单元格”对象中，并且可能导致单元格的重复计数。尽管如此，如果更准确的细胞边界对实验至关重要，则可以使用这种方法。我们鼓励用户在开发更新的分割算法时对其进行试验，并将其合并到此管道中以获得更好的结果。
在开发新的组织流式细胞术 panel 时可能会出现几个问题。首先，不同的荧光标记物产生的荧光量大致相似，这一点至关重要。如果一个荧光基团比另一个荧光基团亮得多，则如果该荧光基团渗入另一个荧光基团，则可能会出现问题，因为渗出可能会超过该通道中的真实染色。如图 3 所示，其中 Alexa Fluor 546 严重渗入 PE-eFluor 610。虽然补偿仍然可以去除这种渗光，但由于未去除焦外光，通常仍会有一些挥之不去的荧光，这可能会导致补偿不完整。此外，显微镜上使用的大多数检测器没有像流式细胞仪那样宽广的动态范围。因此，随着通道中渗出的增加，该检测器中更多的动态范围将被来自其他荧光基团的信号饱和，而来自目标荧光基团的信号将更少。当从具有大量漏通的通道中去除补偿时，可以解析出真实信号;然而，该标志物阳性细胞和阴性细胞之间的差异会变小，并可能导致无法分辨中间状态，甚至可能无法分辨出阴性细胞中的阳性结果。因此，应避免通道之间的重叠。其次，标记物的亮度可以在不同的组织之间发生变化。例如，一组作用于淋巴结的标志物在用于脾脏或中枢神经系统时可能不再起作用，因为标志物可能会变得太亮或太暗，导致该通道过多地渗入其他通道或被其他通道的渗出所淹没。在这种情况下，可能需要切换标记物上的荧光团，或将一抗偶联抗体的使用切换为二抗的使用。最后，当通道之间有过多重叠时，利用标记定位的差异可能很有价值。如果两个通道彼此严重重叠，但一个是核标记，另一个是单元表面标记，则光谱重叠将对彼此的影响最小，因为补偿不会影响相同的体素。如果可能，面板的设计应确保重叠通道的定位不同，或者标志物在单独的细胞上表达。
总体而言，结果表明组织流式细胞术是一种在单细胞水平分析组织学图像的通用技术。虽然较旧的技术可能仅限于分析不直接细胞间接触的细胞，但该分析管道可以分离接触的细胞，使其适用于研究体内平衡或炎症期间免疫细胞聚集在损伤部位的组织中的细胞。

由免疫系统细胞和神经胶质细胞驱动的炎症会导致 CNS 的慢性疾病，其中每个群体都可以促进其他群体的活动 1,2,3。了解免疫系统如何与 CNS 的这些元素相互作用以促进 CNS 炎症是目前感兴趣的主要话题，并且单细胞 RNA 测序等高参数技术极大地促进了这一主题。通过单细胞 RNA 测序，我们发现在几种 CNS 疾病中，神经胶质细胞和免疫系统之间存在广泛的通信 4,5,6。了解这些相互作用如何影响这些疾病对于阐明这些疾病的生物学至关重要。
单细胞测序分析的一个问题是，这些技术需要破坏组织以获得单细胞或细胞核，从而导致空间信息的完全丢失。了解细胞在组织中的位置对于了解细胞在驱动炎症中的作用至关重要。例如，B 细胞等免疫细胞在神经炎症期间可以集中在 CNS 中;然而，它们很少进入 CNS 薄壁组织，而是集中在 CNS 屏障7。鉴于它们的定位，这些细胞不太可能通过与 CNS 薄壁细胞中的神经胶质细胞发生物理相互作用来促进 CNS 炎症，这表明它们可能与神经胶质细胞发生的任何相互作用都会通过分泌因子发生。此外，中枢神经系统疾病中发生的病理通常具有结构 8,9，因此细胞在组织中的定位可以关键地确定它是积极导致疾病还是旁观者。因此，使用空间定向来评估细胞在病理学中的作用是必不可少的。
研究组织中的细胞通常是通过使用免疫组织化学或免疫荧光显微镜来完成的。这些技术的一个问题是，它们通常只能同时对最多四个参数进行成像。这是这些技术的主要限制，因为我们从流式细胞术和单细胞 RNA 测序分析中了解到，许多细胞群需要两个或多个参数进行鉴定;此外，在查找 Cell Type10 的特定子集时，所需的参数数量通常会增加。因此，使用标准成像技术来研究细胞亚群如何在组织内相互作用是不切实际的。
通过可以保留空间信息的较新的高参数方法，例如空间 RNA 测序11 和成像质谱流式细胞术12，已经部分解决了这个问题。虽然这些技术很有价值，但它们确实存在一些问题，例如没有广泛使用、将 3D 数据简化为二维以及需要相当多的专业知识来执行。另一种称为顺序染色的技术，其中组织用一组抗体染色，然后灭活前一组抗体，然后再用另一组抗体染色，无需专用设备或专业知识即可实现高参数组织学 13,14,15.然而，顺序染色可能非常耗费人力，并且需要大量的显微镜检查时间，这对于没有个人显微镜的实验室来说可能不切实际。因此，需要能够扩大荧光参数数量的技术，这些参数可以在广泛可用且及时的显微镜上一次成像。
一旦采集了高参数数据，另一个问题就出现了：传统的图像分析方法不太可能成功分析数据。手动计数或阈值等技术仅在分析由单个参数组成或多个标记具有相同的定位（仅计数重叠信号）时才可行。此限制使传统分析不足以处理高参数数据集。通过从组织学图像中分割单个细胞，然后进行类似流式细胞术的门控策略来识别细胞类型，可以成功分析这些数据集16,17。然而，影响这些分析的另一个问题是，它们仅适用于所有感兴趣的细胞都彼此物理分离的数据集，因为这些技术没有采用可以准确分离物理接触细胞的方法。因此，需要一种更新的方法，即使细胞处于物理接触状态，也可以对组织学切片进行单细胞分析。
在本文中，描述了一种称为组织流式细胞术的简单方案，该方案之前已经介绍过18 ，它扩展了可以使用广泛使用的显微镜同时成像的荧光参数的数量。该方案的工作原理是用光谱重叠染料对组织进行染色，然后使用光谱补偿去除重叠通道的渗出，以获得清晰的单一染色。为了便于分析高参数组织学图像，描述了一个详细的分析管道，该管道从组织切片中提取单个细胞，以便使用类似流式细胞术的门控策略将细胞分选为不同的群体。该方案适用于细胞弥散存在的组织和细胞紧密压实在一起的组织，使该技术可用于研究稳态和神经炎症中的 CNS 等组织。因此，组织流式细胞术是研究复杂细胞类型之间相互作用的有用技术，这些细胞类型需要多个细胞标志物来定义细胞，同时保持空间信息。

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>100% Ethanol</td>
			<td>Sigma</td>
			<td>676829-1L</td>
			<td></td>
		</tr>
		<tr>
			<td>4% PFA</td>
			<td>Electron Microscopy Sciences</td>
			<td>157-4</td>
			<td></td>
		</tr>
		<tr>
			<td>Anaconda</td>
			<td>N/A</td>
			<td>N/A</td>
			<td>https://www.anaconda.com/download</td>
		</tr>
		<tr>
			<td>Bovine Serum Albumin</td>
			<td>Sigma</td>
			<td>A4503-50G</td>
			<td></td>
		</tr>
		<tr>
			<td>Cold fish stain gelatin&#160;</td>
			<td>Sigma</td>
			<td>G7765</td>
			<td></td>
		</tr>
		<tr>
			<td>Collating multichannel data from Imaris.ipynb script</td>
			<td>N/A</td>
			<td>N/A</td>
			<td>https://github.com/elliottcalgary/Histoflow-Cytometry-Analysis-</td>
		</tr>
		<tr>
			<td>Convert FlowJo output to txt file for Cell selection in Imaris.ipynb script</td>
			<td>N/A</td>
			<td>N/A</td>
			<td>https://github.com/elliottcalgary/Histoflow-Cytometry-Analysis-</td>
		</tr>
		<tr>
			<td>Donkey anti-rat Alexa Fluor 647</td>
			<td>JacksonImmunoResearch</td>
			<td>712-605-153</td>
			<td>1:300 concentration</td>
		</tr>
		<tr>
			<td>Donkey anti-rat DyLight 405</td>
			<td>Jackson ImmunoResearch</td>
			<td>712-475-153</td>
			<td>1:200 concentration</td>
		</tr>
		<tr>
			<td>Donkey Serum</td>
			<td>JacksonImmunoResearch</td>
			<td>017-000-001</td>
			<td></td>
		</tr>
		<tr>
			<td>F(ab&#39;)2-Goat anti-Mouse IgG PerCP-eFluor 710</td>
			<td>Thermofisher</td>
			<td>46-4010-82</td>
			<td>1:25 concentration</td>
		</tr>
		<tr>
			<td>FIJI</td>
			<td>N/A</td>
			<td>N/A</td>
			<td>https://imagej.net/software/fiji/</td>
		</tr>
		<tr>
			<td>FlowJo</td>
			<td>FlowJo LLC</td>
			<td></td>
			<td>Software 4</td>
		</tr>
		<tr>
			<td>Fluorescence spectraviewer</td>
			<td></td>
			<td></td>
			<td>https://www.thermofisher.com/order/fluorescence-spectraviewer/#!/</td>
		</tr>
		<tr>
			<td>Fluoromount-G</td>
			<td>Southern Biotech</td>
			<td>0100-01</td>
			<td></td>
		</tr>
		<tr>
			<td>Fresh frozen human tonsil sections</td>
			<td>amsbio</td>
			<td>HF-707</td>
			<td></td>
		</tr>
		<tr>
			<td>Glass coverslip</td>
			<td>VWR</td>
			<td>48393 106</td>
			<td></td>
		</tr>
		<tr>
			<td>Goat anti-human IgA Alexa Fluor 488</td>
			<td>JacksonImmunoResearch</td>
			<td>109-546-011</td>
			<td>1:400 concentration</td>
		</tr>
		<tr>
			<td>Goat anti-human IgG Cy3</td>
			<td>JacksonImmunoResearch</td>
			<td>709-166-098</td>
			<td>1:400 concentration</td>
		</tr>
		<tr>
			<td>Goat anti-human IgM Dylight 405</td>
			<td>JacksonImmunoResearch</td>
			<td>109-476-129</td>
			<td>1:300 concentration</td>
		</tr>
		<tr>
			<td>Goat anti-rabbit A546</td>
			<td>Thermo Fisher Scientific</td>
			<td>A-11035</td>
			<td>1:250 concentration</td>
		</tr>
		<tr>
			<td>Goat anti-rabbit IgG PE-Alexa Fluor 610</td>
			<td>Thermofisher</td>
			<td>A-20981</td>
			<td>1:250 concentration</td>
		</tr>
		<tr>
			<td>Horse Serum</td>
			<td>Sigma</td>
			<td>H1138</td>
			<td></td>
		</tr>
		<tr>
			<td>Ilastik</td>
			<td>N/A</td>
			<td>N/A</td>
			<td>https://www.ilastik.org/</td>
		</tr>
		<tr>
			<td>Ilastik FIJI plugin</td>
			<td>N/A</td>
			<td>N/A</td>
			<td>https://www.ilastik.org/documentation/fiji_export/plugin</td>
		</tr>
		<tr>
			<td>Imaris File Converter</td>
			<td>Oxford Instruments</td>
			<td></td>
			<td>Software 2</td>
		</tr>
		<tr>
			<td>Imaris with cell module</td>
			<td>Oxford Instruments</td>
			<td></td>
			<td>Software 3</td>
		</tr>
		<tr>
			<td>kimwipe</td>
			<td>Kimtech</td>
			<td>34155</td>
			<td></td>
		</tr>
		<tr>
			<td>LasX Life Science software</td>
			<td>Leica</td>
			<td></td>
			<td>Software 1</td>
		</tr>
		<tr>
			<td>Mouse anti-human CD20</td>
			<td>VWR</td>
			<td>CA95024-322</td>
			<td>1:40 concentration</td>
		</tr>
		<tr>
			<td>Mouse anti-human CD38 APC-R700</td>
			<td>BD Biosciences</td>
			<td>564980</td>
			<td>1:20 concentration</td>
		</tr>
		<tr>
			<td>Normal Goat Serum</td>
			<td>JacksonImmunoResearch</td>
			<td>005-000-001</td>
			<td></td>
		</tr>
		<tr>
			<td>Normal Mouse Serum</td>
			<td>JacksonImmunoResearch</td>
			<td>015-000-001</td>
			<td></td>
		</tr>
		<tr>
			<td>Normal Rabbit Serum</td>
			<td>JacksonImmunoResearch</td>
			<td>011-000-001</td>
			<td></td>
		</tr>
		<tr>
			<td>Normal Rat Serum</td>
			<td>JacksonImmunoResearch</td>
			<td>012-000-120</td>
			<td></td>
		</tr>
		<tr>
			<td>Nuclear Yellow</td>
			<td>Abcam</td>
			<td>ab138903</td>
			<td>Dissolve in DMSO at a concentration of 2 mg/ml and store at 4&#176;C in the dark</td>
		</tr>
		<tr>
			<td>PAP pen</td>
			<td>Cedarlane</td>
			<td>MU22</td>
			<td></td>
		</tr>
		<tr>
			<td>PBS</td>
			<td>Gibco</td>
			<td>10010-023</td>
			<td></td>
		</tr>
		<tr>
			<td>Rabbit anti-human Ki67</td>
			<td>Abcam</td>
			<td>ab15580</td>
			<td>1:500 concentration</td>
		</tr>
		<tr>
			<td>Rabbit anti-mouse Iba1</td>
			<td>Wako</td>
			<td>019-19741</td>
			<td>1:500 concentration</td>
		</tr>
		<tr>
			<td>Rat anti-human Blimp1</td>
			<td>Thermofisher</td>
			<td>14-5963-82</td>
			<td>1:40 concentration</td>
		</tr>
		<tr>
			<td>Rat anti-mouse B220 Alexa Fluor 647</td>
			<td>BioLegend</td>
			<td>103226</td>
			<td>1:250 concentration</td>
		</tr>
		<tr>
			<td>Rat anti-mouse CD138</td>
			<td>Biolegend</td>
			<td>142502</td>
			<td>1:200 concentration</td>
		</tr>
		<tr>
			<td>Rat anti-mouse CD3 PE-eFluor 610</td>
			<td>Thermo Fisher Scientific</td>
			<td>61-0032-82</td>
			<td>1:40 concentration</td>
		</tr>
		<tr>
			<td>Rat anti-mouse CD4 Alexa Fluor 488</td>
			<td>BioLegend</td>
			<td>100529</td>
			<td>1:200 concentration</td>
		</tr>
		<tr>
			<td>Rat anti-mouse CD45 allophycocyanin-R700</td>
			<td>BD Biosciences</td>
			<td>565478</td>
			<td>1:50 concentration</td>
		</tr>
		<tr>
			<td>Rat anti-mouse IgD PerCP-eFluor 710</td>
			<td>Thermo Fisher Scientific</td>
			<td>46-5993-82</td>
			<td>1:50 concentration</td>
		</tr>
		<tr>
			<td>SP8 Confocal microscope</td>
			<td>Leica</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Triton X-100</td>
			<td>Sigma</td>
			<td>X100-500ml</td>
			<td></td>
		</tr>
		<tr>
			<td>Trueblack</td>
			<td>Biotium</td>
			<td>23007</td>
			<td></td>
		</tr>
		<tr>
			<td>Tween-20</td>
			<td>Sigma</td>
			<td>P7949-500ml</td>
			<td></td>
		</tr>
		<tr>
			<td>Ultracomp ebeads</td>
			<td>Thermofisher</td>
			<td>01-2222-42</td>
			<td></td>
		</tr>
	</tbody>
</table>

generating and analyzing high-parameter histology images with histoflow cytometry

使用组织学来研究组织切片（例如来自中枢神经系统 （CNS） 的组织切片）中的免疫细胞多样性受到一次可以成像的荧光参数数量的严重限制。大多数免疫细胞亚群是使用流式细胞术通过使用蛋白质标志物的复杂组合来定义的，通常需要四个或更多参数才能最终识别，这超出了大多数传统显微镜的能力。由于流式细胞术会解离组织并丢失空间信息，因此需要能够在询问复杂细胞类型的作用的同时保留空间信息的技术。这些问题在这里通过创建一种方法来解决，该方法通过收集光谱重叠荧光团的信号并使用光谱解混来分离每个单独荧光团的信号来扩展可以成像的荧光参数的数量。然后使用分析管道处理这些图像，以拍摄高参数组织学图像并从这些图像中提取单细胞，以便可以在单细胞水平上分析每个细胞的独特荧光特性。然后，使用类似流式细胞术的设门策略，可以将细胞分析成亚群并定位回组织学切片，不仅可以量化它们的丰度，还可以确定它们如何与组织环境相互作用。总体而言，证明了使用组织流式细胞术在组织学切片中研究复杂免疫群体的简单性和潜力。

<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/66889/66889fig01.jpg"> 图 1：组织流式细胞术工作流程。 组织切片用光谱重叠染料染色（步骤 1）。使用与可调谐带通滤光片配对的单个激发激光器收集图像，以最大限度地减少荧光团之间的光谱渗漏（步骤 2）。通道之间的光谱渗出根据使用单一颜色染色组织对照生成的补偿矩阵（步骤 3）进行校正。然后使用 ilastik（步骤 4）识别图像中的细胞核和细胞，并在软件 3（步骤 5）中分成单个细胞。在将所有数据从软件 3 导出到软件 4 以进行流式细胞术分析之前，会合并其他参数。然后从软件 4 导出细胞身份并映射回原始组织中的细胞 ID，以解析组织切片中细胞的空间定位（步骤 6）。钱币代表需要购买的商业软件，而电脑标志代表自由软件。每个步骤的大致时间显示在沙漏旁边。商业软件列在 材料表中。该图改编自 Jain 等人 18。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/66889/66889fig01large.jpg" target="_blank">请单击此处查看此图的较大版本。</a>
在图 3 中，用大鼠抗小鼠 CD138 抗体与驴抗大鼠 Dylight 405 二抗配对的淋巴结组织染色，Nuclear Yellow、一种与 Alexa Fluor 488 偶联的大鼠抗小鼠 CD4 抗体、一种与 PerCP-eF710 偶联的大鼠抗小鼠 IgD 抗体、一种兔抗小鼠 Iba1 抗体与驴抗兔 Alexa Fluor 546 二抗配对， 一种与 PE-eF610 偶联的大鼠抗小鼠 CD3ε 抗体，一种与 Alexa Fluor 647 偶联的大鼠抗小鼠 B220 抗体，以及一种与 APC-R700 偶联的大鼠抗小鼠 CD45 抗体。使用紫色 405 nm 激光刺激 Dylight 405 和 Nuclear yellow 染料，分别在 408-438 nm 和 460-530 nm 范围内检测到它们的发射。使用绿色 488 nm 激光刺激 Alexa Fluor 488 和 PerCP-eF710 染料，分别在 495-545 nm 和 682-750 nm 范围内检测到它们的发射。使用黄绿色 552 nm 激光刺激 Alexa Fluor 546 和 PE-eF610 染料，分别在 557-600 nm 和 615-652 nm 范围内检测到它们的发射。使用红色 640 nm 激光刺激 Alexa Fluor 647 和 APC-R700 染料，分别在 647-682 nm 和 700-750 nm 范围内检测到它们的发射。
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/66889/66889fig02.jpg"> 图 2：不良和质量补偿示例。 使用与 PE-eFluor 610 偶联的抗体对微珠进行染色，并在对应于 PE-eFluor 610 （PE-eF610） 和 Alexa Fluor 546 （A546） 通道的通道中成像。对 A546 通道中的同一图像应用不同程度的补偿（欠补偿减少 10%，正确补偿减少 28%，过度补偿减少 60%），以去除 PE-eF610 荧光团的渗漏，从而导致不同程度的分离。为了更好地可视化补偿程度，提供了透血图像的增亮版本。黄色箭头指向每个图像中的相同区域，对应于 PE-eF610 通道中存在真实染色的区域。比例尺：4 μm。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/66889/66889fig02large.jpg" target="_blank">请点击此处查看此图的较大版本。</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/66889/66889fig03.jpg"> 图 3：使用染色组织切片进行荧光补偿。（A-C） 淋巴结组织切片用与所列荧光团偶联的单个 Abs 染色。然后对所有通道（A，顶部）对未补偿的单染色样品进行成像，并对单色对照（A，底部）进行补偿。（B） 量化 （A） 中通道之间的渗漏（当前图像的平均荧光强度除以当前荧光团通道的平均荧光强度）并以热图形式呈现。白色方块表示超过 100% 出血的值。（C） 通过比较完全染色样品中 Iba1-A546 和 CD3-PEeF610 的光谱分离，在未补偿和基于细胞的补偿条件下评估光谱重叠。比例尺：30 μm。该图改编自 Jain 等人 18。<a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/66889/66889fig03large.jpg" target="_blank">请单击此处查看此图的较大版本。</a>
通过遵循此方案（ 在图 1 中总结），应有效分离光谱重叠的荧光染料，如图 3A、B 所示。虽然可能无法完全分离染料，但分离应该足以清楚地区分不同的细胞类型（图 3C）。如果另一个通道中仍然存在光谱重叠细胞的阴影，这可能表明仍然存在渗出，并且图像可能需要重新处理（图 2）。此外，如果补偿区域低于与背景染色相关的荧光水平，则过度补偿将很明显，并且会在曾经渗出的地方显示为黑色区域（图 2）。过补偿会导致已应用补偿的通道中丢失实际信号，因此必须避免。尽管如此，如果正确遵循了该协议，则应该不存在补偿问题，因此，研究人员应考虑任何明显的渗漏是人为的还是生物学的一部分。
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/66889/66889fig04.jpg"> 图 4：基于 ilastik 的细胞核和细胞检测示例。 核黄染色（左上）用于识别细胞核（黄色右上）和不是细胞核（蓝色）。代表性 CD45 染色（如左下角所示）用于识别细胞（右下角为黄色）和非细胞（蓝色）。该图改编自 Jain 等人 18。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/66889/66889fig04large.jpg" target="_blank">请单击此处查看此图的较大版本。</a>
一旦染料被准确分离，将组织分裂成单个细胞对于进行单细胞分析至关重要。此处描述的协议使用用户定义的机器学习（图 4）来分离细胞，即使它们紧密压实在一起，如图 6 所示的淋巴结所示。
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/66889/66889fig05.jpg"> 图 5：评估浇口是否已正确调整。 显示了淋巴结中代表性的 CD138 染色（青色），并制作了三个单独的门（左侧的点图）以识别组织中的 CD138 + 细胞。对 CD138 + 细胞的过于保守的估计显示为蓝色门，并以蓝色映射到组织。CD138 + 细胞的平衡估计显示为绿色门，并映射到绿色组织。对 CD138 + 细胞的过于宽松的估计显示为红色门，并以红色映射到组织。黄色圆圈表示 CD138+ 细胞未被过于保守的门识别的区域，洋红色圆圈表示没有 CD138+ 细胞的区域，该区域被过于宽松的门声称包含 CD138+ 细胞。比例尺：30 μm。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/66889/66889fig05large.jpg" target="_blank">请点击此处查看此图的较大版本。</a>
在流式细胞术分析中确定门的精确位置时应小心（如图 5 所示），以确保这些门不会高估或低估细胞的丰度。如图 5 所示，这应该通过将细胞定位回组织来确定，以查看是否在分析中捕获了表达您感兴趣的标记物的细胞。如果选择的细胞过多（例如，不表达 CD138 的细胞被选择为 CD138 + ），则应将门移至不太宽松的程度，如果选择的细胞太少，则应使门更加宽松。门控应针对选择性进行优化，以便首先优化上游门控，然后优化链中的每个后续门控。最后，门控策略的有效优化应该能够解析感兴趣的细胞亚群（图 6 和 图 7）。
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/66889/66889fig06.jpg"> 图 6：基于流式细胞术的组织切片细胞鉴定。 （A） 在软件 4 中分析从软件 3 中导出的淋巴结切片中单个细胞的荧光值，以根据所示的设门策略鉴定规定的细胞群。（B） 将软件 4 中鉴定的群体定位回同一组织切片，并为每个群体生成表面。CD45 染色未显示。比例尺：30 μm。该图改编自 Jain 等人 18。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/66889/66889fig06large.jpg" target="_blank">请单击此处查看此图的较大版本。</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/66889/66889fig07.jpg"> 图 7：小鼠淋巴结中单个染色和种群的细分。 免疫细胞标志物的单个染色剂显示在顶部面板中， 图 6A 中鉴定的其相关门控群体显示在每个单个染色剂的下方。比例尺：30 μm，如左上面板所示。该图改编自 Jain 等人 18。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/66889/66889fig07large.jpg" target="_blank">请单击此处查看此图的较大版本。</a>
该技术以前已被18 用于表征神经炎症期间免疫细胞浸润到脊髓的情况，并验证了使用组织流式细胞术和流式细胞术发现等比例的浸润免疫细胞。该技术也已得到验证，证明它在小鼠脾脏和大脑中起作用，并且可以识别治疗条件之间的差异，这些差异在相同的流式细胞术实验（未发表）中重现。该技术还用于分析接受 CNS 模型立体定向注射的小鼠的脊髓。
<img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/66889/66889fig08.jpg"> 图 8：人扁桃体切片中 8 种染料的分离。 人扁桃体切片用 CD20 染色以识别 B 细胞，用 IgM 、 IgA 和 IgG 染色以识别浆细胞。掺入 Blimp1 和 CD38 染色剂以进一步验证浆细胞身份，并掺入 Ki67 以识别增殖细胞。Nuclear yellow 染色剂未显示在组合图像中。比例尺：22 μm。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/66889/66889fig08large.jpg" target="_blank">请点击此处查看此图的较大版本。</a>
该技术也可用于分析人体组织切片。作为人体组织内染色的一个例子，用 8 种标记物对人扁桃体切片进行染色：与 Dylight 405 偶联的山羊抗人 IgM 抗体、核黄、与 Alexa Fluor 488 偶联的山羊抗人 IgA 抗体、小鼠抗人 CD20 抗体与与 PerCP-eFluor 710 偶联的山羊抗小鼠 F（ab'）2 片段配对， 与 Cy3 偶联的山羊抗人 IgG、兔抗人 Ki67 抗体与与 PE-Alexa Fluor 610 偶联的山羊抗兔抗体配对、大鼠抗人 Blimp1 抗体与与 Alexa Fluor 647 偶联的驴抗大鼠抗体配对，以及与 APC-R700 偶联的小鼠抗人 CD38 抗体。补偿后，可以看到这些标志物在扁桃体切片中的分离（图8）。这证明了该技术在不同组织和物种中的实用性。
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody><tr><td>解决方案名称</td>
			<td colspan="2">组成</td>
			<td colspan="4">制作方法</td>
		</tr><tr><td>封闭缓冲液</td>
			<td colspan="2">10% 马血清、1% BSA 和 0.1% 冷鱼染色明胶的 PBS 溶液</td>
			<td colspan="4">将 5 mL 马血清、0.5 g BSA、50 μL 冷鱼染色明胶添加到 45 mL PBS 中。将这些溶液分装到 15 mL 试管中，并将它们储存在 -20 °C 直至需要。</td>
		</tr><tr><td>Perm 和封闭缓冲液</td>
			<td colspan="2">10% 马血清、1% BSA、0.1% 冷鱼渍明胶、0.1% Triton X-100、0.05% 吐温-20 的 PBS 溶液</td>
			<td colspan="4">添加 5 mL 马血清、0.5 g BSA、50 μL 冷鱼染色明胶、50 μL Triton X-100 和 25 μL Tween-20 至 45 mL PBS。将这些溶液分装到 15 mL 试管中，并将它们储存在 -20 °C 直至需要。</td>
		</tr><tr><td>烫发和染色缓冲液</td>
			<td colspan="2">1% BSA、0.1% 冷鱼染色明胶、0.5% Triton X-100 的 PBS 溶液</td>
			<td colspan="4">将 0.5 g BSA、50 μL 冷鱼染色明胶和 250 μL Triton X-100 添加到 50 mL PBS 中。将这些溶液分装到 15 mL 试管中，并将它们储存在 -20 °C 直至需要。</td>
		</tr><tr><td>淬灭缓冲液</td>
			<td colspan="2">5% Trueblack、66.5% 乙醇、28.5% 水</td>
			<td colspan="4">将 Trueblack 溶液在 70 °C 下预热 5 分钟。然后将 50 μL Trueblack 添加到 950 μL 70% 乙醇中，制成 Trueblack 缓冲液。每次都让它新鲜。每张玻片需要 ~500 μL，但具体量取决于组织的性质。</td>
		</tr><tr><td>染色缓冲液</td>
			<td colspan="2">1% BSA 和 0.1% 冷鱼在 PBS 中染色明胶</td>
			<td colspan="4">将 0.5 g BSA 和 50 μL 冷鱼染色明胶添加到 50 mL PBS 中。将这些溶液分装到 15 mL 试管中，并将它们储存在 -20 °C 直至需要。</td>
		</tr></tbody></table>表 1：组织切片染色所需的溶液及其成分列表。
补充编码文件 1：一个 Python 脚本，用于从每个通道收集荧光值并创建一个摘要文件。<a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/66889/Supplementary%20Coding%20File%201.zip" target="_blank">请点击此处下载此文件。</a>
补充编码文件 2：一个 Python 脚本，用于将门控单元格的所有 ID 号列表创建到文本文件中。<a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/66889/Supplementary%20Coding%20File%202v2.zip" target="_blank">请点击此处下载此文件。</a>

作者聚焦：用于神经科学研究的增强型多重免疫荧光显微镜实验方案

这里描述的是一种可用于通过免疫荧光显微镜对五个或更多荧光参数进行成像的方法。概述了从这些图像中提取单细胞并通过类似流式细胞术的门控策略进行单细胞分析的分析管道，该管道可以识别组织切片中的细胞亚群。

使用 Histoflow 流式细胞术生成和分析高参数组织学图像

The usage of histology to investigate immune cell diversity in tissue sections such as those derived from the central nervous system (CNS) is critically ...

我们的首要目标是研究免疫系统细胞和中枢神经系统内的神经胶质细胞如何促进多发性硬化症等神经系统疾病的发展和进展。免疫荧光显微镜检查是生物学科中广泛使用的标准技术，对神经科学和免疫学研究至关重要。困扰研究人员的主要问题之一是，由于传统显微镜的限制，免疫荧光显微镜通常受限于一次可以成像的探针数量。在该协议中，我们描述了一种扩展许多显微镜一次可以成像的探针数量的方法，并提供了一个分析管道来处理信息密集的图像。该协议的优点是它可以适应许多广泛使用的显微镜并且易于执行，这将使更多的实验室可以使用多重组织学分析。

generating-analyzing-high-parameter-histology-images-with-histoflow

Nanyang Technological University

Research

JoVE Journal

Neuroscience

Generating and Analyzing High-Parameter Histology Images with Histoflow Cytometry

278 次观看.  University of Calgary. 我们的首要目标是研究免疫系统细胞和中枢神经系统内的神经胶质细胞如何促进多发性硬化症等神经系统疾病的发展和进展。免疫荧光显微镜检查是生物学科中广泛使用的标准技术，对神经科学和免疫学研究至关重要。困扰研究人员的主要问题之一是，由于传统显微镜的限制，免疫荧光显微镜通常受限于一次可以成像的探针数量。在该协议中，我们描述了一种扩展许多?...

视频: 作者聚焦：用于神经科学研究的增强型多重免疫荧光显微镜实验方案

Membrane Potentials, Synaptic Responses, Neuronal Circuitry, Neuromodulation and Muscle Histology Using the Crayfish: Student Laboratory Exercises

The purpose of this report is to help develop an understanding of the effects caused by ion gradients across a biological membrane. Two aspects that influence a cell's membrane potential and which we address in these experiments are: (1) Ion concentration of K+ on the outside of the membrane, and (2) the permeability of the membrane to specific ions. The crayfish abdominal extensor muscles are in groupings with some being tonic (slow) and others phasic (fast) in their biochemical and physiological phenotypes, as well as in their structure; the motor neurons that innervate these muscles are correspondingly different in functional characteristics. We use these muscles as well as the superficial, tonic abdominal flexor muscle to demonstrate properties in synaptic transmission. In addition, we introduce a sensory-CNS-motor neuron-muscle circuit to demonstrate the effect of cuticular sensory stimulation as well as the influence of neuromodulators on certain aspects of the circuit. With the techniques obtained in this exercise, one can begin to answer many questions remaining in other experimental preparations as well as in physiological applications related to medicine and health. We have demonstrated the usefulness of model invertebrate preparations to address fundamental questions pertinent to all animals.

The experiments demonstrate an easy approach for students to gain experience in examining muscle structure, synaptic responses, the effects of ion gradients and permeability on membrane potentials. Also, a sensory-CNS-motor-muscle circuit is presented to show a means to test effects of compounds on a neuronal circuit.

膜电位，突触反应，神经回路，神经调节和肌肉组织学用小龙虾:学生实验室练习

The purpose of this report is to help develop an understanding of the effects caused by ion gradients across a biological membrane. Two aspects that ...

科研

神经科学

Combining Lipophilic dye, in situ Hybridization, Immunohistochemistry, and Histology

Going beyond single gene function to cut deeper into gene regulatory networks requires multiple mutations combined in a single animal. Such analysis of two or more genes needs to be complemented with in situ hybridization of other genes, or immunohistochemistry of their proteins, both in whole mounted developing organs or sections for detailed resolution of the cellular and tissue expression alterations. Combining multiple gene alterations requires the use of cre or flipase to conditionally delete genes and avoid embryonic lethality. Required breeding schemes dramatically enhance effort and cost proportional to the number of genes mutated, with an outcome of very few animals with the full repertoire of genetic modifications desired. Amortizing the vast amount of effort and time to obtain these few precious specimens that are carrying multiple mutations necessitates tissue optimization. Moreover, investigating a single animal with multiple techniques makes it easier to correlate gene deletion defects with expression profiles. We have developed a technique to obtain a more thorough analysis of a given animal; with the ability to analyze several different histologically recognizable structures as well as gene and protein expression all from the same specimen in both whole mounted organs and sections. Although mice have been utilized to demonstrate the effectiveness of this technique it can be applied to a wide array of animals. To do this we combine lipophilic dye tracing, whole mount in situ hybridization, immunohistochemistry, and histology to extract the maximal possible amount of data.

Combining Lipophilic dye, in situ Hybridization, Immunohistochemistry, and Histology

A combination of different techniques to maximize data collection from mouse tissue is presented.

结合亲脂性染料，原位杂交，免疫组织化学和组织学

Going beyond single gene function to cut deeper into gene regulatory networks requires multiple mutations combined in a single animal.  Such analysis of ...

Utilizing 3D Printing Technology to Merge MRI with Histology: A Protocol for Brain Sectioning

Magnetic resonance imaging (MRI) allows for the delineation between normal and abnormal tissue on a macroscopic scale, sampling an entire tissue volume three-dimensionally. While MRI is an extremely sensitive tool for detecting tissue abnormalities, association of signal changes with an underlying pathological process is usually not straightforward. In the central nervous system, for example, inflammation, demyelination, axonal damage, gliosis, and neuronal death may all induce similar findings on MRI. As such, interpretation of MRI scans depends on the context, and radiological-histopathological correlation is therefore of the utmost importance. Unfortunately, traditional pathological sectioning of brain tissue is often imprecise and inconsistent, thus complicating the comparison between histology sections and MRI. This article presents novel methodology for accurately sectioning primate brain tissues and thus allowing precise matching between histology and MRI. The detailed protocol described in this article will assist investigators in applying this method, which relies on the creation of 3D printed brain slicers. Slightly modified, it can be easily implemented for brains of other species, including humans.

The overall goal of this protocol is to accurately align magnetic resonance imaging (MRI) image volumes with histology sections via the creation of customized 3D-printed brain holders and slicer boxes.

利用3D打印技术来合并MRI与组织学:一个大脑切片协议

Magnetic resonance imaging (MRI) allows for the delineation between normal and abnormal tissue on a macroscopic scale, sampling an entire tissue volume ...

Mass Histology to Quantify Neurodegeneration in Drosophila

Progressive neurodegenerative diseases like Alzheimer&#39;s disease (AD) or Parkinson&#39;s disease (PD) are an increasing threat to human health worldwide. Although mammalian models have provided important insights into the underlying mechanisms of pathogenicity, the complexity of mammalian systems together with their high costs are limiting their use. Therefore, the simple but well-established Drosophila model-system&#160;provides an alternative for investigating the molecular pathways that are affected in these diseases. Besides behavioral deficits, neurodegenerative diseases are characterized by histological phenotypes such as neuronal death and axonopathy. To quantify neuronal degeneration and to determine how it is affected by genetic and environmental factors, we use a histological approach that is based on measuring the vacuoles in adult fly brains. To minimize the effects of systematic error and to directly compare sections from control and experimental flies in one preparation, we use the &#39;collar&#39; method for paraffin sections. Neurodegeneration is then assessed by measuring the size and/or number of vacuoles that have developed in the fly brain. This can either be done by focusing on a specific region of interest or by analyzing the entire brain by obtaining serial sections that span the complete head. Therefore, this method allows one to measure not only severe degeneration but also relatively mild phenotypes that are only detectable in a few sections, as occurs during normal aging.

Mass Histology to Quantify Neurodegeneration in Drosophila

Drosophila is widely used as a model system to study neurodegeneration. This protocol describes a method by which degeneration, as determined by vacuole formation in the brain, can be quantified. It also minimizes effects due to the experimental procedure by processing and sectioning control and experimental flies as one sample.

大众组织学量化在神经退行性变<em&gt;果蝇</em

Progressive neurodegenerative diseases like Alzheimer&#39;s disease (AD) or Parkinson&#39;s disease (PD) are an increasing threat to human health ...

Analyzing Dendritic Morphology in Columns and Layers

In many regions of the central nervous systems, such as the fly optic lobes and the vertebrate cortex, synaptic circuits are organized in layers and columns to facilitate brain wiring during development and information processing in developed animals. Postsynaptic neurons elaborate dendrites in type-specific patterns in specific layers to synapse with appropriate presynaptic terminals. The fly medulla neuropil is composed of 10 layers and about 750 columns; each column is innervated by dendrites of over 38 types of medulla neurons, which match with the axonal terminals of some 7 types of afferents in a type-specific fashion. This report details the procedures to image and analyze dendrites of medulla neurons. The workflow includes three sections: (i) the dual-view imaging section combines two confocal image stacks collected at orthogonal orientations into a high-resolution 3D image of dendrites; (ii) the dendrite tracing and registration section traces dendritic arbors in 3D and registers dendritic traces to the reference column array; (iii) the dendritic analysis section analyzes dendritic patterns with respect to columns and layers, including layer-specific termination and planar projection direction of dendritic arbors, and derives estimates of dendritic branching and termination frequencies. The protocols utilize custom plugins built on the open-source MIPAV (Medical Imaging Processing, Analysis, and Visualization) platform and custom toolboxes in the matrix laboratory language. Together, these protocols provide a complete workflow to analyze the dendritic routing of Drosophila medulla neurons in layers and columns, to identify cell types, and to determine defects in mutants.

Here, we show how to analyze dendritic routing of Drosophila medulla neurons in columns and layers. The workflow includes a dual-view imaging technique to improve the image quality and computational tools for tracing, registering dendritic arbors to the reference column array and for analyzing the dendritic structures in 3D space.

分析树突状形态的列和图层

In many regions of the central nervous systems, such as the fly optic lobes and the vertebrate cortex, synaptic circuits are organized in layers and ...

Live Images of GLUT4 Protein Trafficking in Mouse Primary Hypothalamic Neurons Using Deconvolution Microscopy

Type 2 diabetes mellitus (T2DM) is a global health crisis which is characterized by insulin signaling impairment and chronic inflammation in peripheral tissues. The hypothalamus in the central nervous system (CNS) is the control center for energy and insulin signal response regulation. Chronic inflammation in peripheral tissues and imbalances of certain chemokines (such as CCL5, TNF&#945;, and IL-6) contribute to diabetes and obesity. However, the functional mechanism(s) connecting chemokines and hypothalamic insulin signal regulation still remain unclear.
In vitro primary neuron culture models are convenient and simple models which can be used to investigate insulin signal regulation in hypothalamic neurons. In this study, we introduced exogeneous GLUT4 protein conjugated with GFP (GFP-GLUT4) into primary hypothalamic neurons to track GLUT4 membrane translocation upon insulin stimulation. Time-lapse images of GFP-GLUT4 protein trafficking were recorded by deconvolution microscopy, which allowed users to generate high-speed, high-resolution images without damaging the neurons significantly while conducting the experiment. The contribution of CCR5 in insulin regulated GLUT4 translocation was observed in CCR5 deficient hypothalamic neurons, which were isolated and cultured from CCR5 knockout mice. Our results demonstrated that the GLUT4 membrane translocation efficiency was reduced in CCR5 deficient hypothalamic neurons after insulin stimulation.

This protocol describes a technique for observation of real-time Green Fluorescence Protein (GFP) tagged Glucose Transporter 4 (GLUT4) protein trafficking upon insulin stimulation and characterization of the biological role of CCR5 in the insulin&#8211;GLUT4 signaling pathway with Deconvolution Microscopy.

用反褶积显微镜观察小鼠原发性下丘脑神经元 GLUT4 蛋白的动态图像

Type 2 diabetes mellitus (T2DM) is a global health crisis which is characterized by insulin signaling impairment and chronic inflammation in peripheral ...

Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software

Measuring neural activity and connectivity associated with cognitive functions at high spatial and temporal resolutions is an important goal in cognitive neuroscience. Intracranial electroencephalography (EEG) can directly record electrical neural activity and has the unique potential to accomplish this goal. Traditionally, averaging analysis has been applied to analyze intracranial EEG data; however, several new techniques are available for depicting neural activity and intra- and inter-regional connectivity. Here, we introduce two analytical protocols we recently applied to analyze intracranial EEG data using the Statistical Parametric Mapping (SPM) software: time-frequency SPM analysis for neural activity and dynamic causal modeling of induced responses for intra- and inter-regional connectivity. We report our analysis of intracranial EEG data during the observation of faces as representative results. The results revealed that the inferior occipital gyrus (IOG) showed gamma-band activity at very early stages (110 ms) in response to faces, and both the IOG and amygdala showed rapid intra- and inter-regional connectivity using various types of oscillations. These analytical protocols have the potential to identify the neural mechanisms underlying cognitive functions with high spatial and temporal profiles.

We present two analytical protocols that can be used to analyze intracranial electroencephalography data using the Statistical Parametric Mapping (SPM) software: time-frequency statistical parametric mapping analysis for neural activity, and dynamic causal modeling of induced responses for intra- and inter-regional connectivity.

利用 SPM 软件分析颅内脑电图数据的神经活动和连接性

Measuring neural activity and connectivity associated with cognitive functions at high spatial and temporal resolutions is an important goal in cognitive ...

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI)

Most methods for conducting meta-analysis of voxel-based neuroimaging studies do not assess whether effects are not null, but whether there is a convergence of peaks of statistical significance, and reduce the assessment of the evidence to a binary classification exclusively based on p-values (i.e., voxels can only be &ldquo;statistically significant&rdquo; or &ldquo;non-statistically significant&rdquo;). Here, we detail how to conduct a meta-analysis using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI), a novel method that uses a standard permutation test to assess whether effects are not null. We also show how to grade the strength of the evidence according to a set of criteria that considers a range of statistical significance levels (from more liberal to more conservative), the amount of data or the detection of potential biases (e.g., small-study effect and excess of significance). To exemplify the procedure, we detail the conduction of a meta-analysis of voxel-based morphometry studies in obsessive-compulsive disorder, and we provide all the data already extracted from the manuscripts to allow the reader to replicate the meta-analysis easily. SDM-PSI can also be used for meta-analyses of functional magnetic resonance imaging, diffusion tensor imaging, position emission tomography and surface-based morphometry studies.

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI

We detail how to conduct a meta-analysis of voxel-based neuroimaging studies using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI).

使用基于种子的 d 映射对基于体素的神经成像研究进行元分析，并结合主题图像的排列 （SDM-PSI）

Most methods for conducting meta-analysis of voxel-based neuroimaging studies do not assess whether effects are not null, but whether there is a ...

Visualizing and Analyzing Intracellular Transport of Organelles and Other Cargos in Astrocytes

Astrocytes are among the most abundant cell types in the adult brain, where they play key roles in a multiplicity of functions. As a central player in brain homeostasis, astrocytes supply neurons with vital metabolites and buffer extracellular water, ions, and glutamate. An integral component of the &#8220;tri-partite&#8221; synapse, astrocytes are also critical in the formation, pruning, maintenance, and modulation of synapses. To enable these highly interactive functions, astrocytes communicate among themselves and with other glial cells, neurons, the brain vasculature, and the extracellular environment through a multitude of specialized membrane proteins that include cell adhesion molecules, aquaporins, ion channels, neurotransmitter transporters, and gap junction molecules. To support this dynamic flux, astrocytes, like neurons, rely on tightly coordinated and efficient intracellular transport. Unlike neurons,&#160;where intracellular trafficking has been extensively delineated, microtubule-based transport in astrocytes has been less studied. Nonetheless, exo- and endocytic trafficking of cell membrane proteins and intracellular organelle transport orchestrates astrocytes&#8217; normal biology, and these processes are often affected in disease or in response to injury. Here we present a straightforward protocol to culture high quality murine astrocytes, to fluorescently label astrocytic proteins and organelles of interest, and to record their intracellular transport dynamics using time-lapse confocal microscopy. We also demonstrate how to extract and quantify relevant transport parameters from the acquired movies using available image analysis software (i.e., ImageJ/FIJI) plugins.

Here we describe an in vitro live-imaging method to visualize intracellular transport of organelles and trafficking of plasma membrane proteins in murine astrocytes. This protocol also presents an image analysis methodology to determine cargo transport itineraries and kinetics.

可视化和分析星形细胞中细胞内器官和其他货物的细胞内传输

Astrocytes are among the most abundant cell types in the adult brain, where they play key roles in a multiplicity of functions. As a central player in ...

Dissection of Single Skeletal Muscle Fibers for Immunofluorescent and Morphometric Analyses of Whole-Mount Neuromuscular Junctions

The neuromuscular junction (NMJ) is a specialized point of contact between the motor nerve and the skeletal muscle. This peripheral synapse exhibits high morphological and functional plasticity. In numerous nervous system disorders, NMJ is an early pathological target resulting in neurotransmission failure, weakness, atrophy, and even in muscle fiber death. Due to its relevance, the possibility to quantitatively assess certain aspects of the relationship between NMJ components can help to understand the processes associated with its assembly/disassembly. The first obstacle when working with muscles is to gain the technical expertise to quickly identify and dissect without damaging their fibers. The second challenge is to utilize high-quality detection methods to obtain NMJ images that can be used to perform quantitative analysis. This article presents a step-by-step protocol for dissecting extensor digitorum longus and soleus muscles from rats. It also explains the use of immunofluorescence to visualize pre and postsynaptic elements of whole-mount NMJs. Results obtained demonstrate that this technique can be used to establish the microscopic anatomy of the synapsis and identify subtle changes in the status of some of its components under physiological or pathological conditions.

The ability to accurately detect neuromuscular junction components is crucial in evaluating modifications in its architecture because of pathological or developmental processes. Here we present a complete description of a straightforward method to obtain high-quality images of whole-mount neuromuscular junctions that can be used to perform quantitative measurements.

单骨骼肌肉纤维解剖，用于全山神经肌肉结的免疫荧光和形态分析

The neuromuscular junction (NMJ) is a specialized point of contact between the motor nerve and the skeletal muscle. This peripheral synapse exhibits high ...

使用 Histoflow 流式细胞术生成和分析高参数组织学图像

副本

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此视频中的章节

膜电位，突触反应，神经回路，神经调节和肌肉组织学用小龙虾:学生实验室练习

结合亲脂性染料，原位杂交，免疫组织化学和组织学

利用3D打印技术来合并MRI与组织学:一个大脑切片协议

大众组织学量化在神经退行性变

分析树突状形态的列和图层

用反褶积显微镜观察小鼠原发性下丘脑神经元 GLUT4 蛋白的动态图像

利用 SPM 软件分析颅内脑电图数据的神经活动和连接性

使用基于种子的 d 映射对基于体素的神经成像研究进行元分析，并结合主题图像的排列（SDM-PSI）

可视化和分析星形细胞中细胞内器官和其他货物的细胞内传输

单骨骼肌肉纤维解剖，用于全山神经肌肉结的免疫荧光和形态分析

使用 Histoflow 流式细胞术生成和分析高参数组织学图像

副本

摘要

探索更多视频

此视频中的章节

膜电位，突触反应，神经回路，神经调节和肌肉组织学用小龙虾:学生实验室练习

结合亲脂性染料，原位杂交，免疫组织化学和组织学

利用3D打印技术来合并MRI与组织学:一个大脑切片协议

大众组织学量化在神经退行性变

分析树突状形态的列和图层

用反褶积显微镜观察小鼠原发性下丘脑神经元 GLUT4 蛋白的动态图像

利用 SPM 软件分析颅内脑电图数据的神经活动和连接性

使用基于种子的 d 映射对基于体素的神经成像研究进行元分析，并结合主题图像的排列 （SDM-PSI）

可视化和分析星形细胞中细胞内器官和其他货物的细胞内传输

单骨骼肌肉纤维解剖，用于全山神经肌肉结的免疫荧光和形态分析

使用基于种子的 d 映射对基于体素的神经成像研究进行元分析，并结合主题图像的排列（SDM-PSI）