作者感谢所有同意并为这项研究捐赠样本的女性。

研究内容和方案已通过深圳市中山泌尿外科医院研究伦理委员会的伦理审查和批准。参与研究的所有女性（20-40 岁）都对样本收集和使用提供了知情同意。
1.病理组织的获取
<ol><li>准备用于组织采集的工具，即测量尺、镊子、包埋盒、包埋纸和纸巾篮。</li>
	<li>观察使用移液管的标准方法收集的子宫内膜组织（比绿豆大）的数量是否足够。</li>
	<li>用镊子将福尔马林的子宫内膜组织转移到包埋纸上，并用尺子测量子宫内膜组织尺寸。</li>
	<li>用包埋纸包裹子宫内膜组织，然后放入包埋盒中。</li>
	<li>将包埋盒放入纸巾篮中进行脱水。</li>
</ol>2.组织脱水
<ol><li>将组织篮放入脱水机的反应室中（参见 材料表），并开始常规组织脱水程序：福尔马林100分钟;福尔马林100分钟;75%酒精60分钟;85% 酒精 60 分钟;95% 酒精 60 分钟;100%酒精60分钟;100%酒精60分钟;100%酒精60分钟;二甲苯35分钟;二甲苯20分钟;二甲苯20分钟;蜡80分钟;蜡80分钟;打蜡 80 分钟。该过程大约需要15小时。</li>
	<li>在组织脱水程序结束时，打开脱水机的反应室，取出组织篮。</li>
</ol>3. 组织包埋
<ol><li>根据试样尺寸取出合适的包埋模具，在70°C下填充石蜡。</li>
	<li>快速将纸巾放入模具中并仔细调整，使纸巾位于模具的中心。</li>
	<li>将模具平稳地移动到冷却板上，轻轻按压纸巾，同时底部的石蜡凝固。</li>
	<li>将包埋盒放在模具顶部，并加满更多的蜡。</li>
	<li>将模具放在冷却板上，当石蜡完全凝固时，将带有连接盒的块从模具上取下。</li>
</ol>4. 组织切片
<ol><li>将块插入切片机的样品夹上，将刀片放入支架中，调整块平面与刀片之间的角度，将切片厚度调整为4μm，转动手轮，开始切片。</li>
	<li>通过从块上切下几片薄片来暴露适当的组织表面。用刷子取出连续和完整的部分。</li>
	<li>当切出足够多的断面时，停止转动手轮，用镊子去除前端不合格的断面，用镊子和刷子将切片漂浮在水浴中的42°C水面上。</li>
	<li>将部分完全压平后，在防分离载玻片上挑选部分，并转移到65°C的载玻片加热器中烘烤60分钟。</li>
	<li>烘烤完成后，将载玻片从载玻片加热器中取出。</li>
</ol>5.免疫组化染色
<ol><li>用抗体稀释剂将一抗稀释到工作溶液中。详见 表1 。</li>
	<li>将稀释后的抗体溶液放入专用试剂瓶中，将检测试剂盒放入全自动IHC染色仪的试剂室中（见 材料表）。</li>
	<li>将载玻片放在载玻片支架上，用特殊的盖子覆盖，然后将它们插入仪器的实验反应室中。</li>
	<li>仪器自动识别载玻片上的试剂和实验信息后，点击开始按钮 开始 免疫组化染色。实验持续约3小时。</li>
</ol>6.载玻片的脱水和密封
<ol><li>免疫组化染色后，取出载玻片支架，取下专用盖板，将染色的载玻片放入载玻片支架中，用清水洗去载玻片上残留的染料。</li>
	<li>将载玻片架转移到自动盖玻片机上（参见 材料表），选择并运行脱水和密封程序。</li>
	<li>脱水密封后取出载玻片。</li>
</ol>7. 扫描载玻片
<ol><li>将载玻片放在全景病理图像扫描仪的载玻片架上（见 材料表），放入仪器载玻片扫描舱进行全景病理图像扫描。扫描需要 2 分钟。请参阅 图 1。</li>
</ol>8. 图像分析
<ol><li>导入图像<ol><li>打开病理图像分析软件（参见 材料表）并创建一个新文件夹。导入要分析的免疫组织化学图像。</li>
	</ol></li>
	<li>构建组织分类器<ol><li>标记多个组织和空白注释，以训练和建立分类器，分别用于识别组织和空白区域。</li>
		<li>使用实时调优，在标记标注过程中实时观察软件的识别能力。如果识别不及时，则备注注释并再次训练，直到组织识别准确。</li>
	</ol></li>
	<li>构建分析算法<ol><li>根据实验类型在软件中选择标准算法：多重 IHC。</li>
		<li>通过选择典型的负像素和正像素来设置单元格识别的颜色参数。 在此基础上，设置细胞核、细胞质、细胞膜的参数，实时观察细胞识别情况，直到找到最适合图像的参数。</li>
		<li>设置阳性细胞识别阈值，实时观察识别情况，直到调整到合适的阈值。</li>
		<li>在算法中选择组织分类器，在组织分类器中检查组织部分，从而在组织的基础上识别细胞。至此，分析算法的建立就完成了。</li>
	</ol></li>
	<li>运行图像分析<ol><li>选择分析区域。使用已建立的算法分析图像。</li>
	</ol></li>
	<li>软件分析完成后，手动检查图像识别是否准确，包括组织识别、阴性和阳性细胞识别。</li>
	<li>如果图像识别不准确，请重新调整算法和参数阈值，重新运行图像分析，直到成功。导出分析结果。请参阅 图 1。</li>
	<li>其他免疫细胞也可以按照上述步骤进行分析（见图1）。根据不同子宫内膜免疫标志物（CD56+uNK细胞、Foxp3+Tregs、CD68+巨噬细胞、CD163+M2巨噬细胞、CD1a+DCs和CD8+T细胞25,26）的实际表达设置不同的分析参数。</li>
	<li>通过软件的计算，得到子宫内膜免疫细胞的比例（见 表2）。用它来评估复发性流产患者子宫内膜中各种免疫细胞的水平。</li>
</ol>

免疫组织化学染色的子宫内膜组织的图像分析

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作者没有什么可透露的。

该协议建立了数字免疫组化图像分析平台，以定量分析RM患者的子宫内膜免疫细胞。在这里，检测了六种子宫内膜免疫标志物，以评估RM患者的子宫内膜免疫微环境。
黄体中期的接受性子宫内膜是成功植入和怀孕的关键27,28。因此，评估子宫内膜免疫细胞百分比在估计子宫内膜容受性方面起着重要作用。通过传统的病理学方法进行子...

复发性流产（RM）是指连续两次或两次以上妊娠的流产，是一种复杂的疾病，近年来引起了临床医生的关注。育龄妇女RM的发病率为1%-5%1。既往研究结果表明，免疫因子与RM 2,3,4,5的发病机制密切相关。维持母胎界面的免疫稳态是胚胎植入和发育所必需的。子宫内膜免疫细胞在维持这种稳态方面发挥多种调节作用，例如促进滋养层侵袭、重塑螺旋动脉和促进胎盘发育 6,7,8,9。
RM 女性的子宫内膜免疫细胞异常既往已有报道。结果显示，高密度子宫自然杀伤细胞 （uNK） 与 RM10、11、12 的发生密切相关。据报道，与活产女性相比，RM女性子宫内膜中的巨噬细胞数量有所增加13。调节性T细胞（Treg）在母体对胚胎的免疫耐受中发挥作用，其水平和功能在RM患者的蜕膜中降低14。细胞毒性 T 细胞 （CTL） 和树突状细胞 （DC） 也在妊娠的免疫调节中发挥作用15,16。因此，对黄体中期局部子宫内膜免疫细胞进行全面的定量分析有助于更好地了解RM的发病机制。目前一些用于子宫内膜免疫细胞定量分析的方法使用流式细胞术，它可以准确地标记具有多种标记物的免疫细胞17,18。然而，流式细胞术的临床应用受到限制，因为它只能在新鲜组织上进行。只有当存在大量多余肿瘤时，获得新鲜组织才可行，这在子宫内膜中很少见。免疫组化可以很好地原位观察组织形态，也可以标记各种免疫细胞，而传统的免疫组化技术无法对免疫细胞进行定量分析。
与常规免疫组化实验相比，子宫内膜免疫细胞的定量免疫组化分析具有重要的临床意义。IHC强度评分通常采用四分制或病理诊断和研究中的强弱排序19,20,21。然而，这种半定量技术是主观的、高度不准确的，并显示出显著的观察者内部和观察者间变异性22。一种可能的解决方案是机器学习的应用，这在数字图像分析中很有价值23,24。通过提供定量测量，这种方法可以更精确地评估子宫组织内的免疫细胞浸润、分布和密度。这种定量信息可以帮助阐明月经周期和各种病理条件下免疫细胞群的动态变化。总体而言，通过免疫组化定量分析子宫内膜中免疫细胞的能力为了解子宫的免疫微环境提供了有价值的见解。
因此，该方案旨在开发和验证一种数字免疫组化图像分析平台，以定量分析RM患者黄体中期的子宫内膜免疫细胞，包括uNK细胞、Tregs、巨噬细胞、DC和细胞毒性T细胞。

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Automated coverslipper</td>
			<td>Sakuraus</td>
			<td>DRS-Prisma-P-JCS&#38;Film-JC2</td>
			<td></td>
		</tr>
		<tr>
			<td>CD163</td>
			<td>GrowGn Biotechnology</td>
			<td>NCL-L-CD163</td>
			<td></td>
		</tr>
		<tr>
			<td>CD1a</td>
			<td>Gene Tech</td>
			<td>GM357129</td>
			<td></td>
		</tr>
		<tr>
			<td>CD56</td>
			<td>Gene Tech</td>
			<td>GT200529</td>
			<td></td>
		</tr>
		<tr>
			<td>CD8</td>
			<td>Novocastra</td>
			<td>NCL-L-CD8-4B11</td>
			<td></td>
		</tr>
		<tr>
			<td>Dehydrator</td>
			<td>Thermo Fisher</td>
			<td>Excelsior ES</td>
			<td></td>
		</tr>
		<tr>
			<td>Digital pathology and</td>
			<td>Indica labs</td>
			<td>HALO</td>
			<td></td>
		</tr>
		<tr>
			<td>Foxp3</td>
			<td>YILIFANG biological</td>
			<td>14-477-82</td>
			<td></td>
		</tr>
		<tr>
			<td>IHC stainer</td>
			<td>Leica</td>
			<td>BOND III</td>
			<td></td>
		</tr>
		<tr>
			<td>Image analysis platform</td>
			<td>Indica labs</td>
			<td>HALO</td>
			<td></td>
		</tr>
		<tr>
			<td>Slide Scanner</td>
			<td>Olympus life science</td>
			<td>VS200</td>
			<td></td>
		</tr>
	</tbody>
</table>

platform for quantitative detection of endometrial immune cells based on immunohistochemistry and digital image analysis

为评估复发性流产（RM）患者的子宫内膜免疫微环境，开发并验证了数字免疫组化图像分析平台，用于定量分析黄体中期子宫内膜免疫细胞。所有子宫内膜样本均在月经周期的黄体中期采集。将石蜡包埋的子宫内膜组织切片成4 μm厚的载玻片，进行免疫组化（IHC）染色检测子宫内膜免疫细胞，包括CD56+ uNK细胞、Foxp3+ Tregs、CD163+ M2巨噬细胞、CD1a+ DCs和CD8+ T细胞。使用数字玻片扫描仪对全景玻片进行扫描，并使用商业图像分析系统进行定量分析。子宫内膜免疫细胞的百分比是通过除以总子宫内膜细胞中的免疫细胞数来计算的。使用商用图像分析系统，可以轻松准确地分析传统图像分析难以或不可能分析的子宫内膜免疫细胞的定量评估。该方法可用于定量表征子宫内膜微环境，包括免疫细胞之间的相互作用，以及不同生殖失败患者的异质性。子宫内膜免疫细胞定量评估平台对RM患者的诊断和治疗具有重要的临床意义。

Recurrent miscarriage (RM) is the loss of two or more consecutive pregnancies and is a complex disease drawing attention from clinicians in recent years.The incidence rate of RM in women of childbearing age is 1%-5% 1. Results of previous studies show that immune factors are closely associated with the pathogenesis of RM2,3,4,5. Maintaining immune homeostasis at the maternal-fetal interface is required for embryo implantation and development. Endometrial immune cells perform several regulatory roles to maintain this homeostasis, such as promoting trophoblast invasion, remodeling spiral arteries, and contributing to placenta development6,7,8,9.
Aberrant endometrial immune cells in women with RM have previously been reported. Results show a close association between the high density of uterine natural killer cells (uNKs) and the occurrence of RM10,11,12. An increased number of macrophages has been reported in the endometrium of women with RM, compared with those who had a live birth13. Regulatory T cells (Treg) play a role in maternal immune tolerance toward the embryo, and their level and function are decreased in the decidua of RM patients14. Cytotoxicity T cells (CTL) and dendritic cells (DCs) also play a role in the immune regulation of pregnancy15,16. Therefore, a comprehensive quantitative analysis of local endometrial immune cells during the mid-luteal phase could help to better understand the pathogenesis of RM. Some current methods for quantitative analysis of endometrial immune cells use flow cytometry which can accurately label immune cells with multiple markers17,18. However, clinical application of flow cytometry is limited because it can only be performed on fresh tissue. Obtaining fresh tissue is only feasible when a large volume of excess tumor is available, a rare occurrence for endometrium. Immunohistochemistry can observe tissue morphology well in situ and can also label various immune cells, while traditional immunohistochemical techniques cannot perform quantitative analysis of immune cells.
Compared to conventional immunohistochemistry experiments, quantitative immunohistochemical analysis of immune cells in the endometrium has important clinical significance. IHC intensity scoring is usually ranked on a four-point scale or strong and weak in pathological diagnostics and research19,20,21. However, this semi-quantitative technique is subjective, highly inaccurate, and demonstrates significant intra-observer and inter-observer variability22. One possible solution is the application of machine learning, which is valuable indigital image analysis23,24. By providing quantitative measurements, this approach enables a more precise assessment of immune cell infiltration, distribution, and density within the uterine tissue. This quantitative information can help to elucidate the dynamic changes in immune cell populations during the menstrual cycle and in various pathological conditions. Overall, the ability to quantitatively analyze immune cells in the endometrium through immunohistochemistry offers valuable insights into the immune microenvironment of the uterus.
Therefore, the protocol aimed to developed and validated a digital immunohistochemistry image analysis platform to quantitatively analyze endometrial immune cells including uNK cells, Tregs, macrophages, DCs and cytotoxic T cells during the mid-luteal phase in RM patients.

作者聚焦：通过子宫内膜免疫细胞定量评估方案推进生殖免疫学 

基于免疫组化和数字图像分析的子宫内膜免疫细胞定量检测平台

Currently, it is challenging to stabilize the analysis within a certain range. It is also difficult to maintain the quality control of the experiment. Our research can help the patients with abnormal endometrial sensitivity in immune to find the cause of reproductive failure.The local proportion of immune cells in the endometrial can be stably and repeatedly detected. Our findings may promote the research progress of the endometrial sensitivity evaluation in patients with repeated implantation failure.

为了定量评估子宫内膜免疫细胞，减少人为操作失误带来的不稳定性，利用免疫组化自动检测和数字定量评价系统，建立了子宫内膜免疫细胞数字化定量分析平台。建立免疫组化图像分析平台，定量分析复发性流产（RM）患者植入窗口期的子宫内膜免疫细胞。所有子宫内膜组织均在月经周期的黄体中期收集。将石蜡包埋的子宫内膜组织切片成4 μm厚的载玻片，进行IHC染色检测子宫内膜免疫细胞，包...

Watch this Scientific Journal Video about Advancing Reproductive Immunology with a Protocol for the Quantitative Evaluation of Endometrial Immune Cells at JoVE.com

本文开发并验证了数字免疫组化图像分析平台，用于定量分析复发性流产患者在植入窗口期的子宫内膜免疫细胞。

To evaluate the endometrial immune microenvironment of patients with recurrent miscarriage (RM), a digital immunohistochemistry image analysis platform ...

目前，将分析稳定在一定范围内具有挑战性。保持实验的质量控制也很困难。我们的研究可以帮助免疫内膜敏感性异常的患者找到生殖衰竭的原因。子宫内膜内免疫细胞的局部比例可以稳定、反复地检测。本研究结果可促进反复着床失败患者子宫内膜敏感性评估的研究进展。

platform-for-quantitative-detection-endometrial-immune-cells-based-on

Research

JoVE Journal

Biology

Platform for Quantitative Detection of Endometrial Immune Cells Based on Immunohistochemistry and Digital Image Analysis

743 次观看.  Shenzhen Zhongshan Urology Hospital. 目前，将分析稳定在一定范围内具有挑战性。保持实验的质量控制也很困难。我们的研究可以帮助免疫内膜敏感性异常的患者找到生殖衰竭的原因。子宫内膜内免疫细胞的局部比例可以稳定、反复地检测。本研究结果可促进反复着床失败患者子宫内膜敏感性评估的研究进展。