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Record W4402625008 · doi:10.1016/j.canrad.2024.07.002

Combination of radiotherapy and immunotherapy in duality with the protumoral action of radiation

2024· review· en· W4402625008 on OpenAlexafffund
Benoît Paquette, Ayman Oweida

Bibliographic record

VenueCancer/Radiothérapie · 2024
Typereview
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsUniversité de Sherbrooke
FundersFonds de Recherche du Québec - Santé
KeywordsRadiation therapyDuality (order theory)Action (physics)ImmunotherapyRadiationMedicineCancer researchImmunologyPhysicsRadiologyMathematicsImmune systemPure mathematicsOptics

Abstract

fetched live from OpenAlex

Radiotherapy is widely used to treat various cancers. Its combination with immune checkpoint inhibitors is intensively studied preclinically and clinically. Although the first results were very encouraging, the number of patients who respond positively remains low, and the therapeutic benefit is often temporary. This review summarizes how radiation can stimulate an antitumor immune response and its combination with immunotherapy based on inhibiting immune checkpoints. We will provide an overview of radiotherapy parameters that should be better controlled to avoid downregulating the antitumor immune response. The low response rate of combining radiotherapy and immunotherapy could, at least in part, be caused by the stimulation of cancer cell invasion and metastasis development that occur at similar doses and number of radiation fractions. To end on a positive note, we explore how a targeted inhibition of the inflammatory cytokines induced by radiation with a cyclooxygenase-2 inhibitor could both support an antitumor immune response and block radiation-induced metastasis formation.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.976
Threshold uncertainty score0.947

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.373
Teacher spread0.329 · 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 designOther design
Domainnot available
GenreReview

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

Citations3
Published2024
Admission routes2
Has abstractyes

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