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嗜酸性粒细胞激活状态的扩散映射。

Diffusion Mapping of Eosinophil-Activation State.

机构信息

Swansea University Medical School, Swansea University, Swansea, SA2 8PP, UK.

Systems and Process Engineering Centre, College of Engineering, Swansea University, Swansea, SA1 8EN, UK.

出版信息

Cytometry A. 2020 Mar;97(3):253-258. doi: 10.1002/cyto.a.23884. Epub 2019 Aug 31.

Abstract

Eosinophils are granular leukocytes that play a role in mediating inflammatory responses linked to infection and allergic disease. Their activation during an immune response triggers spatial reorganization and eventual cargo release from intracellular granules. Understanding this process is important in diagnosing eosinophilic disorders and in assessing treatment efficacy; however, current protocols are limited to simply quantifying the number of eosinophils within a blood sample. Given that high optical absorption and scattering by the granular structure of these cells lead to marked image features, the physical changes that occur during activation should be trackable using image analysis. Here, we present a study in which imaging flow cytometry is used to quantify eosinophil activation state, based on the extraction of 85 distinct spatial features from dark-field images formed by light scattered orthogonally to the illuminating beam. We apply diffusion mapping, a time inference method that orders cells on a trajectory based on similar image features. Analysis of exogenous cell activation using eotaxin and endogenous activation in donor samples with elevated eosinophil counts shows that cell position along the diffusion-path line correlates with activation level (99% confidence level). Thus, the diffusion mapping provides an activation metric for each cell. Assessment of activated and control populations using both this spatial image-based, activation score and the integrated side-scatter intensity shows an improved Fisher discriminant ratio r = 0.7 for the multivariate technique compared with an r = 0.47 for the traditional whole-cell scatter metric. © 2019 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

摘要

嗜酸性粒细胞是一种颗粒状白细胞,在介导与感染和过敏疾病相关的炎症反应中发挥作用。在免疫反应过程中,它们的激活会触发空间重排,并最终导致细胞内颗粒中的货物释放。了解这一过程对于诊断嗜酸性粒细胞疾病和评估治疗效果非常重要;然而,目前的方案仅限于简单地定量血液样本中的嗜酸性粒细胞数量。鉴于这些细胞的颗粒结构具有高光学吸收率和散射率,导致明显的图像特征,因此在激活过程中发生的物理变化应该可以通过图像分析来跟踪。在这里,我们提出了一项研究,该研究使用成像流式细胞术来量化嗜酸性粒细胞的激活状态,方法是从与照明光束正交散射形成的暗场图像中提取 85 个独特的空间特征。我们应用扩散映射,这是一种时间推断方法,它根据相似的图像特征对细胞进行排序。使用 eotaxin 对外源细胞的激活和供体样本中升高的嗜酸性粒细胞计数的内源性激活进行分析表明,细胞沿着扩散路径线的位置与激活水平相关(置信度为 99%)。因此,扩散映射为每个细胞提供了一个激活指标。使用这种基于空间图像的激活评分和集成侧散射强度评估激活和对照群体,与传统的全细胞散射指标相比,多元技术的 Fisher 判别比 r = 0.7 提高,而传统的全细胞散射指标 r = 0.47。2019 年,作者。流式细胞术由 Wiley 期刊出版公司代表国际先进细胞技术协会出版。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2750/7079009/411536f2ced4/CYTO-97-253-g001.jpg

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