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Record W4210679360 · doi:10.1080/2162402x.2022.2033433

CD4+ T cells in classical Hodgkin lymphoma express exhaustion associated transcription factors TOX and TOX2

2022· article· en· W4210679360 on OpenAlexafffund
J. E. Veldman, Jéssica Rodrigues Plaça, Lauren C. Chong, Miente Martijn Terpstra, Mirjam F. Mastik, Léon C.L.T. van Kempen, Klaas Kok, Tomohiro Aoki, Christian Steidl, Anke van den Berg, Lydia Visser, Arjan Diepstra

Bibliographic record

VenueOncoImmunology · 2022
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsUniversity of British ColumbiaSpinal Cord Injury BC
FundersRijksuniversiteit GroningenCanadian Cancer Society Research InstituteUniversitair Medisch Centrum GroningenGenome British ColumbiaGenome Canada
KeywordsImmune systemAntigenBiologyPopulationT cellCancer researchLymphomaImmunologyMolecular biologyMedicine

Abstract

fetched live from OpenAlex

, which were amongst the 100 significantly enriched genes in comparison with the CD4+CD26+ T cells. Findings were validated in single-cell RNA sequencing data from an independent cohort. Interestingly, immunohistochemistry revealed predominant and high frequency of staining for TOX and TOX2 in the T cells attached to the tumor cells. In conclusion, the dominant CD4+CD26- T cell population in cHL is antigen experienced, polyclonal, and exhausted. This population is likely a main contributor to the very high response rates to immune checkpoint inhibitors in cHL.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.933
Threshold uncertainty score0.620

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.253
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations34
Published2022
Admission routes2
Has abstractyes

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