Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing 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
18 authors.
Archit VermaInstitute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA.ORCID 0000-0003-2318-1011
Changhua YuDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.ORCID 0000-0003-4799-4535
Stefanie BachlSchool of Medicine, University of California, San Francisco, San Francisco,CA, USA.
Ivan LopezSchool of Medicine, Stanford University, Stanford, California, USA.ORCID 0000-0002-7071-5277
Morgan SchwartzDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.ORCID 0000-0001-8131-9125
Erick MoenDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.ORCID 0000-0002-5947-7044
Nupura KaleSchool of Medicine, University of California, San Francisco, San Francisco,CA, USA.ORCID 0000-0002-3185-8646
Carter ChingSchool of Medicine, University of California, San Francisco, San Francisco,CA, USA.
Geneva MillerDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.ORCID 0000-0001-6910-3559
Tom DoughertyDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.ORCID 0000-0001-8025-0330
Ed PaoDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.ORCID 0009-0006-9964-1781
William GrafDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
Carl WardGladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA.
Siddhartha JenaStem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts, USA.
Alex MarsonSchool of Medicine, University of California, San Francisco, San Francisco,CA, USA.
Julia CarnevaleSchool of Medicine, University of California, San Francisco, San Francisco,CA, USA.ORCID 0000-0001-9410-7148
David Van ValenDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.ORCID 0000-0001-7534-7621
Barbara E EngelhardtInstitute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA.ORCID 0000-0002-6139-7334
Funding
The Cellular Geography of Therapeutic Resistance in CancerU2CCA233195 · NCI · DANA-FARBER CANCER INST · PI JOHNSON, BRUCE E. · 2018 to 2023
$13.7M
A kinetic framework to map the genetic determinants of alternative RNA isoform expressionR01HG012967 · NHGRI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI Barbara Engelhardt, Athma A Pai · 2023 to 2026
$3.0M
Methods to build and annotate tissue atlases using spatial genomic dataR01HG013736 · NHGRI · J. DAVID GLADSTONE INSTITUTES · PI Barbara Engelhardt · 2024 to 2026
T cell therapies, such as chimeric antigen receptor (CAR) T cells and T cell receptor (TCR) T cells, are a growing class of anti-cancer treatments. However, expansion to novel indications and beyond last-line treatment requires engineering cells' dynamic population behaviors. Here we develop the tools for
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.
Cellular behavior analysis from live-cell imaging of TCR T cell-cancer cell interactions. · full record | OpenQuestion