کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5513543 1541214 2017 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Application of imaging flow cytometry for characterization of acute inflammation in non-classical animal model systems
ترجمه فارسی عنوان
استفاده از جریان سیاتومتر تصویربرداری برای تعیین التهاب حاد در سیستم های مدل غیر حیوانات غیر کلاسیک
موضوعات مرتبط
علوم زیستی و بیوفناوری بیوشیمی، ژنتیک و زیست شناسی مولکولی زیست شیمی
چکیده انگلیسی


- Multi-parametric approach for phagocytosis analysis based on imaging flow cytometry (IFC).
- Focus on antimicrobial responses by avian leukocytes following in vivo challenge.
- IFC provided added depth for examination of phagocyte subsets.
- Show new opportunities for evaluation of inflammation control in non-classical animal models.

Phagocytes display marked heterogeneity in their capacity to induce and control acute inflammation. This has a significant impact on the effectiveness of antimicrobial immune responses at different tissue sites as well as their predisposition for inflammation-associated pathology. Imaging flow cytometry provides novel opportunities for characterization of these phagocyte populations through high spatial resolution, statistical robustness, and a broad range of quantitative morphometric cell analysis tools. This study highlights an integrative approach that brings together new tools in imaging flow cytometry with conventional methodologies for characterization of phagocyte responses during acute inflammation. We focus on a comparative avian in vivo challenge model to showcase the added depth gained through these novel quantitative multiparametric approaches even in the absence of antibody-based cellular markers. Our characterization of acute inflammation in this model shows significant conservation of phagocytic capacity among avian phagocytes compared to other animal models. However, it also highlights evolutionary divergence with regards to phagocyte inflammation control mechanisms based on the internalization of apoptotic cells.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Methods - Volume 112, 1 January 2017, Pages 167-174
نویسندگان
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