Article in European journal of immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
11 authors.
Jet van den DijsselSanquin Research and Landsteiner Laboratory, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.ORCID 0000-0002-4849-0374
Tejas MenonDepartment of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia.ORCID 0000-0001-7636-0051
Hayley A McQuiltenDepartment of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia.
Oliver EltheringtonDepartment of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia.
Alexis GonzalezDepartment of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia.
Sevana BaghdasarianDepartment of Chemical and Biomolecular Engineering, University of California Los Angeles, Los Angeles, California, USA.
Citradewi SoemardyDepartment of Bioengineering, University of California Los Angeles, Los Angeles, California, USA.
Dino Di CarloDepartment of Bioengineering, University of California Los Angeles, Los Angeles, California, USA.
Klaas P J M van GisbergenSanquin Research and Landsteiner Laboratory, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.ORCID 0000-0003-3623-7555
Anja Ten BrinkeSanquin Research and Landsteiner Laboratory, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
Carolien E van de SandtDepartment of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia.ORCID 0000-0002-4155-7433
Funding
Australian Research Council DE220100185Chan Zuckerberg Initiative Silicon Valley Community Foundation 2023-332386Stichting Sanquin Bloedvoorziening L2506University of Melbourne Establishment_Grant
6 · The paper itself
Abstract
To link IFNγ-secretion levels of epitope-specific T-cells with their TCRαβ, we coated nanovials with pHLA-I to capture and activate epitope-specific T-cells and their secreted IFNγ, followed by index-sorting and TCRαβ sequencing. We demonstrate that nanovials are a promising tool to link single epitope-specific TCRαβ clonotypes to the cell's functional properties.
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.
Linking Epitope-Specific T-Cell Receptors to IFNγ Secretion Using Nanovial Technology. · full record | OpenQuestion