Characterization of cellular immunity using TruAI technology for in vitro fluorescent image analysis 2246

Abstract Description Rapid profiling of cellular immune responses is essential for vaccine development. Traditionally, flow cytometry and enzyme-linked immunosorbent spot (ELISpot) assays are used to determine cellular immune response to vaccination after antigen restimulation in vitro. As an alternative, we have evaluated a novel fluorescence microscopy platform with TruAI-enabled software to characterize T-cell responses efficiently. Adult Balb/c mice were vaccinated intranasally with a self-attenuated influenza virus vaccine at least six weeks before spleens were collected for analysis. Splenocytes were stimulated in vitro with PBS (negative control), PHA (positive control), or influenza virus nuclear protein peptides for 24 hours. Stimulated cells were then labeled with fluorochrome conjugated monoclonal antibodies (anti CD4+, CD8+, IFN-γ, IL4), as well as DAPI for nuclei staining. Fixed cells were then imaged using an Olympus APEX APX100-HCU fluorescent microscope with cellSense APEX software. Preliminary results show increased CD4+ IFN-γ-positive and CD4+ IL4-positive cells in influenza vaccinated samples, suggesting an enhanced Th1 and Th2 immune responses in vaccinated mice. Utilizing the TruAIfeature, we calibrated the software’s neural network to accurately count cell populations, improving reliability and efficiency in immunological profiling. This provided a rapid and efficient method to determine cellular immune response after vaccination. Funding Sources Supported by research grant from Eunice Kennedy Shriver National Institute of Child Health and Human Development (HD109732). Topic Categories Technological Innovations in Immunology (TECH)

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Publication Details

Journal
The Journal of Immunology
Published
2025-11-01
DOI
https://doi.org/10.1093/jimmun/vkaf283.185
Primary Topic
Cell Image Analysis Techniques
Type
article
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article

Characterization of cellular immunity using TruAI technology for in vitro fluorescent image analysis 2246

Mingtao Zeng, Bernardo David Olivares Olivares, Yanping Chen, Antonio Muñoz
The Journal of Immunology
Cell Image Analysis Techniques
article

Characterization of cellular immunity using TruAI technology for in vitro fluorescent image analysis 2246

Mingtao Zeng, Bernardo David Olivares Olivares, Yanping Chen, Antonio Muñoz
article en

Abstract

Abstract Description Rapid profiling of cellular immune responses is essential for vaccine development. Traditionally, flow cytometry and enzyme-linked immunosorbent spot (ELISpot) assays are used to determine cellular immune response to vaccination after antigen restimulation in vitro. As an alternative, we have evaluated a novel fluorescence microscopy platform with TruAI-enabled software to characterize T-cell responses efficiently. Adult Balb/c mice were vaccinated intranasally with a self-attenuated influenza virus vaccine at least six weeks before spleens were collected for analysis. Splenocytes were stimulated in vitro with PBS (negative control), PHA (positive control), or influenza virus nuclear protein peptides for 24 hours. Stimulated cells were then labeled with fluorochrome conjugated monoclonal antibodies (anti CD4+, CD8+, IFN-γ, IL4), as well as DAPI for nuclei staining. Fixed cells were then imaged using an Olympus APEX APX100-HCU fluorescent microscope with cellSense APEX software. Preliminary results show increased CD4+ IFN-γ-positive and CD4+ IL4-positive cells in influenza vaccinated samples, suggesting an enhanced Th1 and Th2 immune responses in vaccinated mice. Utilizing the TruAIfeature, we calibrated the software’s neural network to accurately count cell populations, improving reliability and efficiency in immunological profiling. This provided a rapid and efficient method to determine cellular immune response after vaccination. Funding Sources Supported by research grant from Eunice Kennedy Shriver National Institute of Child Health and Human Development (HD109732). Topic Categories Technological Innovations in Immunology (TECH)

The Journal of ImmunologyVol. 214(Supplement_1)
Texas Tech University (US), Texas Tech University Health Sciences Center (US)
Openalex Percentile: Top 75%
Cell Image Analysis Techniques
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