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Shifting the equilibrium in cancer immunoediting: from tumor tolerance to eradication

2011· review· en· W1881296535 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueImmunological Reviews · 2011
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsnot available
FundersNational Cancer InstituteCanadian Institutes of Health ResearchCancer Research UKHoward Hughes Medical Institute
KeywordsImmunoeditingEffectorImmune systemTumor microenvironmentBiologyCell biologyCancer researchImmunologyImmunotherapy

Abstract

fetched live from OpenAlex

The continual interaction of the immune system with a developing tumor is thought to result in the establishment of a dynamic state of equilibrium. This equilibrium depends on the balance between effector and regulatory T-cell compartments. Whereas regulatory T cells can infiltrate and accumulate within tumors, effector T cells fail to efficiently do so. Furthermore, effector T cells that do infiltrate the tumor become tightly controlled by different regulatory cellular subsets and inhibitory molecules. The outcome of this balance is critical to survival, and whereas in some cases the equilibrium can rapidly result in the elimination of the transformed cells by the immune system, in many other cases the tumor manages to escape immune control. In this review, we discuss relevant work focusing on the establishment of the intratumor balance, the dynamic changes in the populations of effector and regulatory T cells within the tumor, and the role of the tumor vasculature and its activation state in the recruitment of different T-cell subsets. Finally, we also discuss work associated to the manipulation of the immune response to tumors and its impact on the infiltration, accumulation, and function of tumor-reactive lymphocytes within the tumor microenvironment.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.011

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 head0.119
GPT teacher head0.356
Teacher spread0.237 · 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