T Cell Analysis
T Cell Analysis - Related Videos
09:32
Cell Cycle Analysis
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2023
Cell cycle refers to the set of events through which a cell grows, replicates its genome, and ultimately divides into two daughter cells through the process of mitosis. Because the amount of DNA in a cell shows characteristic changes throughout the cycle, techniques known as cell cycle analysis can be used to separate a population of cells according to the different phases of cell cycle they are in, based on their varying DNA content.This video will cover the principles behind cell cycle...
12:19
Analysis of Cell Cycle Position in Mammalian Cells
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Cited by 71 •
2012
Determining the cell cycle position of a population of cells, or understanding how signals affect proliferation, can be readily measured by flow cytometry using this protocol. We report a simple experimental approach to staining cells and quantifying their position in the cell cycle.
07:27
Transcriptome Analysis of Single Cells
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Cited by 72 •
2011
In this article we describe a simple method for the harvesting of single cells from rat primary neuronal cultures and subsequent transcriptome analysis using aRNA amplification. This approach is generalizable to any cell type.
10:54
Quantitative Analysis of Cell Edge Dynamics during Cell Spreading
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Cited by 3 •
2021
In this protocol, we present the experimental procedures of a cell spreading assay that is based on live-cell microscopy. We provide an open-source computational tool for the unbiased segmentation of fluorescently labeled cells and quantitative analysis of lamellipodia dynamics during cell spreading.
06:17
Analysis of Multidimensional Microscopy Data Using Cell-ACDC
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2025
Accurate analysis of multidimensional microscopy data requires complex workflows. This article demonstrates how to use the software Cell-ACDC. It leverages state-of-the-art AI-driven models for segmentation, tracking, cell pedigree analysis, and quantification of microscopy data. Crucially, it complements these models with an innovative framework for semi-automated correction of the models' output.
FAQs
The two major T cell subsets provide complementary information about adaptive immune responses. CD4+ cells help characterize coordination of immune activity, whereas CD8+ cells are examined for functions associated with eliminating infected targets, including cytotoxic activity. Separating these populations during analysis helps researchers determine whether an infection, vaccine, or treatment produces a balanced or subset-specific response.
Stimulation creates a defined condition for evaluating T cell responsiveness. Antigen-directed stimulation examines responses linked to a particular pathogen or immune target, while mitogens provide a broader activation condition. Comparing resulting cytokine production, proliferation, or cytotoxic activity helps distinguish functional capacity from the baseline abundance or identity of T cells in a sample.
Surface markers can indicate cellular identity and activation state, while intracellular cytokine measurements provide evidence of cytokine-producing function. Proliferation shows whether cells expand after stimulation, and cytotoxicity assays assess the ability to carry out target-cell killing. Using several readouts together gives a more complete interpretation than relying on a single cellular measurement.
Flow cytometry can characterize individual cells through surface markers and intracellular cytokines, allowing researchers to relate function to defined T cell populations. Immunoassays provide a complementary way to measure immune-related signals in the tested material. Related techniques extend this assessment to outcomes such as proliferation or cytotoxic activity, depending on the experimental question.
A study generally begins by exposing T cells to antigen or mitogen, followed by measurement of selected response features. Researchers may assess surface identity markers, intracellular cytokines, proliferation, or cytotoxic activity using flow cytometry, immunoassays, or related methods. The resulting data are then interpreted across CD4+ and CD8+ populations to connect phenotype with function.
Its applications include evaluating host defense, vaccine responses, immune deficiencies, chronic infections, and immunotherapies. Measurements can also help identify cellular biomarkers associated with disease progression or treatment outcomes. In these settings, comparing T cell abundance, activation, and function provides evidence for how immune responses change with infection, vaccination, disease, or therapeutic intervention.