Paul D. Smith , Karen J. McLean , Michael A. Murphy , Yvette Wilson , Mark Murphy , Ann M. Turnley , Mark J. Cook
{"title":"荧光免疫组织化学中抗原丰度定量评估的一种基于亮度-面积-产物的方案","authors":"Paul D. Smith , Karen J. McLean , Michael A. Murphy , Yvette Wilson , Mark Murphy , Ann M. Turnley , Mark J. Cook","doi":"10.1016/j.brainresprot.2005.02.004","DOIUrl":null,"url":null,"abstract":"<div><p>A problem frequently facing researchers examining abundance of expression of a given antigen is measurement. When the antigen is confined to the nucleus, absolute numbers of nuclei or a percentage of nuclei expressing the antigen in a given region can be estimated. When the antigen is localized to cytoplasm, cytoplasmic organelles or processes or membranes, the assessment becomes more difficult. In these settings, an observer/experimenter may assign a density score but intra- and inter-observer agreement using a three-tiered system, and finer resolution than this, is unlikely to be reproducible. Digital image analysis provides an opportunity to minimize observer bias in quantification of immunohistochemical staining<span>. Previously, reported digital methods have mostly employed chromogen-staining methods and often report mean image brightness. We report a method for quantitatively assessing and expressing abundance of expression of an antigen in neural tissue stained with immunofluorescent methods by determining the brightness-area-product (BAP). The described protocol utilizes simple to use commercially available software and calculates BAP rather than mean brightness as a measure more representative of antigen abundance and visual interpretation. Accordingly, we propose this protocol as a useful adjunct to observer interpretation of fluorescent immunohistochemistry and its application to assessment of antigen abundance for varying patterns of antigen localization.</span></p></div>","PeriodicalId":79477,"journal":{"name":"Brain research. Brain research protocols","volume":"15 1","pages":"Pages 21-29"},"PeriodicalIF":0.0000,"publicationDate":"2005-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.brainresprot.2005.02.004","citationCount":"15","resultStr":"{\"title\":\"A brightness-area-product-based protocol for the quantitative assessment of antigen abundance in fluorescent immunohistochemistry\",\"authors\":\"Paul D. Smith , Karen J. McLean , Michael A. Murphy , Yvette Wilson , Mark Murphy , Ann M. Turnley , Mark J. Cook\",\"doi\":\"10.1016/j.brainresprot.2005.02.004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>A problem frequently facing researchers examining abundance of expression of a given antigen is measurement. When the antigen is confined to the nucleus, absolute numbers of nuclei or a percentage of nuclei expressing the antigen in a given region can be estimated. When the antigen is localized to cytoplasm, cytoplasmic organelles or processes or membranes, the assessment becomes more difficult. In these settings, an observer/experimenter may assign a density score but intra- and inter-observer agreement using a three-tiered system, and finer resolution than this, is unlikely to be reproducible. Digital image analysis provides an opportunity to minimize observer bias in quantification of immunohistochemical staining<span>. Previously, reported digital methods have mostly employed chromogen-staining methods and often report mean image brightness. We report a method for quantitatively assessing and expressing abundance of expression of an antigen in neural tissue stained with immunofluorescent methods by determining the brightness-area-product (BAP). The described protocol utilizes simple to use commercially available software and calculates BAP rather than mean brightness as a measure more representative of antigen abundance and visual interpretation. Accordingly, we propose this protocol as a useful adjunct to observer interpretation of fluorescent immunohistochemistry and its application to assessment of antigen abundance for varying patterns of antigen localization.</span></p></div>\",\"PeriodicalId\":79477,\"journal\":{\"name\":\"Brain research. Brain research protocols\",\"volume\":\"15 1\",\"pages\":\"Pages 21-29\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.brainresprot.2005.02.004\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Brain research. 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A brightness-area-product-based protocol for the quantitative assessment of antigen abundance in fluorescent immunohistochemistry
A problem frequently facing researchers examining abundance of expression of a given antigen is measurement. When the antigen is confined to the nucleus, absolute numbers of nuclei or a percentage of nuclei expressing the antigen in a given region can be estimated. When the antigen is localized to cytoplasm, cytoplasmic organelles or processes or membranes, the assessment becomes more difficult. In these settings, an observer/experimenter may assign a density score but intra- and inter-observer agreement using a three-tiered system, and finer resolution than this, is unlikely to be reproducible. Digital image analysis provides an opportunity to minimize observer bias in quantification of immunohistochemical staining. Previously, reported digital methods have mostly employed chromogen-staining methods and often report mean image brightness. We report a method for quantitatively assessing and expressing abundance of expression of an antigen in neural tissue stained with immunofluorescent methods by determining the brightness-area-product (BAP). The described protocol utilizes simple to use commercially available software and calculates BAP rather than mean brightness as a measure more representative of antigen abundance and visual interpretation. Accordingly, we propose this protocol as a useful adjunct to observer interpretation of fluorescent immunohistochemistry and its application to assessment of antigen abundance for varying patterns of antigen localization.