Masahiro Ono @ Tocky Lab
@monotockylab.bsky.social
Immunologist | Creator and Developer of Tocky | Integrative Experimental and Computational Immunology | T cells | Cancer Immunology | Immunotherapy
Imperial College London, Reader
Website: monotockylab.github.io
GitHub: github.com/MonoTockyLab
Imperial College London, Reader
Website: monotockylab.github.io
GitHub: github.com/MonoTockyLab
Reposted by Masahiro Ono @ Tocky Lab
Bored of black-box UMAP and clustering in #Cytometry?
GatingTree skips such methods, directly analyses high-dimensional data, builds reproducible tree paths across markers, and reveals group-specific effects.
No dimensionality reduction, just interpretable gates. 🌳
GatingTree skips such methods, directly analyses high-dimensional data, builds reproducible tree paths across markers, and reveals group-specific effects.
No dimensionality reduction, just interpretable gates. 🌳
July 13, 2025 at 12:25 PM
Bored of black-box UMAP and clustering in #Cytometry?
GatingTree skips such methods, directly analyses high-dimensional data, builds reproducible tree paths across markers, and reveals group-specific effects.
No dimensionality reduction, just interpretable gates. 🌳
GatingTree skips such methods, directly analyses high-dimensional data, builds reproducible tree paths across markers, and reveals group-specific effects.
No dimensionality reduction, just interpretable gates. 🌳
Bored of black-box UMAP and clustering in #Cytometry?
GatingTree skips such methods, directly analyses high-dimensional data, builds reproducible tree paths across markers, and reveals group-specific effects.
No dimensionality reduction, just interpretable gates. 🌳
GatingTree skips such methods, directly analyses high-dimensional data, builds reproducible tree paths across markers, and reveals group-specific effects.
No dimensionality reduction, just interpretable gates. 🌳
July 13, 2025 at 12:25 PM
Bored of black-box UMAP and clustering in #Cytometry?
GatingTree skips such methods, directly analyses high-dimensional data, builds reproducible tree paths across markers, and reveals group-specific effects.
No dimensionality reduction, just interpretable gates. 🌳
GatingTree skips such methods, directly analyses high-dimensional data, builds reproducible tree paths across markers, and reveals group-specific effects.
No dimensionality reduction, just interpretable gates. 🌳
Message:
- Foxp3⁺ T cells are part of a broader spectrum of self-reactive T cells.
- HTLV-1 can transform this broader pool into leukemic cells.
- Analysis of the dynamics of Foxp3 and TCR signalling is key, instead of relying on 'Treg', an inflexible concept.(4/4)
academic.oup.com/discovimmuno...?
- Foxp3⁺ T cells are part of a broader spectrum of self-reactive T cells.
- HTLV-1 can transform this broader pool into leukemic cells.
- Analysis of the dynamics of Foxp3 and TCR signalling is key, instead of relying on 'Treg', an inflexible concept.(4/4)
academic.oup.com/discovimmuno...?
Spectrum of Treg and self-reactive T cells: single cell perspectives from old friend HTLV-1
Summary. Despite extensive regulatory T cell (Treg) research, fundamental questions on in vivo dynamics remain to be answered. The current study aims to di
academic.oup.com
April 26, 2025 at 12:41 PM
Message:
- Foxp3⁺ T cells are part of a broader spectrum of self-reactive T cells.
- HTLV-1 can transform this broader pool into leukemic cells.
- Analysis of the dynamics of Foxp3 and TCR signalling is key, instead of relying on 'Treg', an inflexible concept.(4/4)
academic.oup.com/discovimmuno...?
- Foxp3⁺ T cells are part of a broader spectrum of self-reactive T cells.
- HTLV-1 can transform this broader pool into leukemic cells.
- Analysis of the dynamics of Foxp3 and TCR signalling is key, instead of relying on 'Treg', an inflexible concept.(4/4)
academic.oup.com/discovimmuno...?
What are self-reactive T cells? Self-reactivity is a vaguely defined concept.
To be quantitative, here is our working model: Self-reactive T cells receive cognate antigen signals in the absence of inflammation or infection, and become Timer⁺ in the Nr4a3-Tocky system(3/4)
rupress.org/jcb/article/...
To be quantitative, here is our working model: Self-reactive T cells receive cognate antigen signals in the absence of inflammation or infection, and become Timer⁺ in the Nr4a3-Tocky system(3/4)
rupress.org/jcb/article/...
April 26, 2025 at 12:32 PM
What are self-reactive T cells? Self-reactivity is a vaguely defined concept.
To be quantitative, here is our working model: Self-reactive T cells receive cognate antigen signals in the absence of inflammation or infection, and become Timer⁺ in the Nr4a3-Tocky system(3/4)
rupress.org/jcb/article/...
To be quantitative, here is our working model: Self-reactive T cells receive cognate antigen signals in the absence of inflammation or infection, and become Timer⁺ in the Nr4a3-Tocky system(3/4)
rupress.org/jcb/article/...
Recent single-cell data support that HTLV-1 transforms activated T cells into leukemia cells by accelerating the activation of spontaneously activated T cells, irrespective of Foxp3.
Thus, ATL is better modelled as a cancer of self-reactive T cells, rather than 'Treg cancer' — but why? (2/4)
Thus, ATL is better modelled as a cancer of self-reactive T cells, rather than 'Treg cancer' — but why? (2/4)
April 26, 2025 at 12:25 PM
Recent single-cell data support that HTLV-1 transforms activated T cells into leukemia cells by accelerating the activation of spontaneously activated T cells, irrespective of Foxp3.
Thus, ATL is better modelled as a cancer of self-reactive T cells, rather than 'Treg cancer' — but why? (2/4)
Thus, ATL is better modelled as a cancer of self-reactive T cells, rather than 'Treg cancer' — but why? (2/4)