Author

Fatemeh Gholizadeh

Concordia University

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Biology Disciplines

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Immunology· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 2 Research Focus:host-pathogen & immune response· 2 Organism:human· 2 Assay:proteomics· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Assay:flow cytometry· 1

Frequent Co-Authors

Eric Han· 2 shared Mehri HajiaghayiiD· 2 shared Niloufar RahbariiD· 2 shared Peter John DarlingtoniD· 2 shared Samuel R. LittleiD· 2 shared Steve C. C. ShihiD· 2 shared Abbas Rahimi Foroushani· 1 shared Ali Mohammad Banaei‐MoghaddamiD· 1 shared

Activity by Year

2018-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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2 shared papersImmunology

Eric Han

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Author profile →

3 papers

Recent·Most cited

Modulatory Effects of M3 Muscarinic Acetylcholine Receptor on Inflammatory Profiles of Human Memory T Helper Cells

Fatemeh Gholizadeh, Mehri Hajiaghayi, Jennifer S. Choi, Samuel R. Little, Niloufar Rahbari, Melika Kargar, Kelly Brotto, Eric Han, Steve C. C. Shih, Peter John Darlington

This study shows that M3R activation in memory Th cells increases pro-inflammatory cytokines like IFN-γ and IL-17A while reducing IL-4, suggesting M3R as a target for modulating immune responses.

The Journal of Immunology · May 22, 2025Peer-reviewedImmunology

β2-Adrenergic Biased Agonist Inhibits the Development of Th17 and the Response of Memory Th17 Cells in an NF-κB-Dependent Manner.

Mehri Hajiaghayi, Fatemeh Gholizadeh, Eric Han, Samuel R. Little, Niloufar Rahbari, Isabella Ardila, Carolina Lopez Naranjo, Kasra Tehranimeh, Steve C. C. Shih, Peter John Darlington

This study shows that nebivolol, a β2-adrenergic biased agonist, suppresses IL-17A production by memory Th17 cells through a non-canonical β2AR signaling pathway involving NF-κB inhibition.

Frontiers in Immunology · Oct 9, 2024Peer-reviewedImmunology

A relative comparison between Hidden Markov- and Log-Linear- based models for differential expression analysis in a real time course RNA sequencing data

Fatemeh Gholizadeh, Zahra Salehi, Ali Mohammad Banaei‐Moghaddam, Abbas Rahimi Foroushani, Kaveh Kavousi

The paper compares EBSeq-HMM and multiDE models for differential expression analysis in time course RNA-seq data, finding multiDE identifies more benchmark DEGs and agrees better with them.

bioRxiv · Oct 22, 2018 · PreprintBioinformatics