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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作者没有财务利益冲突。

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?...

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...

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

Research

JoVE Journal

Neuroscience

Generating and Analyzing High-Parameter Histology Images with Histoflow Cytometry

291 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 ...

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 ...

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 ...

小鼠视网膜 OCT 纤维图与共聚焦图像的比对

Alignment of Visible-Light Optical Coherence Tomography Fibergrams with Confocal Images of the Same Mouse Retina

In recent years, in vivo retinal imaging, which provides non-invasive, real-time, and longitudinal information about biological systems and processes, has been increasingly applied to obtain an objective assessment of neural damage in eye diseases. Ex vivo confocal imaging of the same retina is often necessary to validate the in vivo findings especially in animal research. In this study, we demonstrated a method for aligning an ex vivo confocal image of the mouse retina with its in vivo images. A new clinical-ready imaging technology called visible light optical coherence tomography fibergraphy (vis-OCTF) was applied to acquire in vivo images of the mouse retina. We then performed the confocal imaging of the same retina as the &#34;gold standard&#34; to validate the in vivo vis-OCTF images. This study not only enables further investigation of the molecular and cellular mechanisms but also establishes a foundation for a sensitive and objective evaluation of neural damage in vivo.

作者聚焦：用于改善青光眼诊断和治疗的体内和离体视网膜成像的进展 

The present protocol outlines the steps for aligning in vivo visible-light optical coherence tomography fibergraphy (vis-OCTF) images with ex vivo confocal images of the same mouse retina for the purpose of verifying the observed retinal ganglion cell axon bundle morphology in the in vivo images.

可见光光学相干断层扫描光纤图与同一小鼠视网膜的共聚焦图像的对齐

In recent years, in vivo retinal imaging, which provides non-invasive, real-time, and longitudinal information about biological systems and processes, has ...