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Record W4386277037 · doi:10.1016/j.celrep.2023.113047

Molecular, metabolic, and functional CD4 T cell paralysis in the lymph node impedes tumor control

2023· article· en· W4386277037 on OpenAlexafffund
Mengdi Guo, Diala Abd-Rabbo, Bruna C. Bertol, Madeleine Carew, Sabelo Lukhele, Laura M. Snell, Wenxi Xu, Giselle M. Boukhaled, Heidi Elsaesser, Marie Jo Halaby, Naoto Hirano, Tracy L. McGaha, David G. Brooks

Bibliographic record

VenueCell Reports · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
FundersNational Institute of Allergy and Infectious DiseasesCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsCd4 t cellCancer researchCD8EffectorParalysisImmunotherapyBiologyT cellCell biologyImmunologyMedicineImmune system

Abstract

fetched live from OpenAlex

CD4 T cells are central effectors of anti-cancer immunity and immunotherapy, yet the regulation of CD4 tumor-specific T (T TS ) cells is unclear. We demonstrate that CD4 T TS cells are quickly primed and begin to divide following tumor initiation. However, unlike CD8 T TS cells or exhaustion programming, CD4 T TS cell proliferation is rapidly frozen in place by a functional interplay of regulatory T cells and CTLA4. Together these mechanisms paralyze CD4 T TS cell differentiation, redirecting metabolic circuits, and reducing their accumulation in the tumor. The paralyzed state is actively maintained throughout cancer progression and CD4 T TS cells rapidly resume proliferation and functional differentiation when the suppressive constraints are alleviated. Overcoming their paralysis established long-term tumor control, demonstrating the importance of rapidly crippling CD4 T TS cells for tumor progression and their potential restoration as therapeutic targets.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
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 head0.008
GPT teacher head0.213
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), 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

Citations15
Published2023
Admission routes2
Has abstractyes

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