MétaCan
Menu
Back to cohort
Record W3180566976 · doi:10.1080/09553002.2021.1956005

Reconciling two opposing effects of radiation therapy: stimulation of cancer cell invasion and activation of anti-cancer immunity

2021· review· en· W3180566976 on OpenAlexafffund
Ayman Oweida, Benoît Paquette

Bibliographic record

VenueInternational Journal of Radiation Biology · 2021
Typereview
Languageen
FieldMedicine
TopicEffects of Radiation Exposure
Canadian institutionsUniversité de Sherbrooke
FundersFonds de Recherche du Québec - Santé
KeywordsImmunityRadiation therapyCancerStimulationCancer researchMedicineCancer therapyCancer cellCell mediated immunityImmunologyOncologyBiologyImmune systemInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: The damage caused by radiation therapy to cancerous and normal cells inevitably leads to changes in the secretome profile of pro and anti-inflammatory mediators. The inflammatory response depends on the dose of radiation and its fractionation, while the inherent radiosensitivity of each patient dictates the intensity and types of adverse reactions. This review will present an overview of two apparently opposite reactions that may occur after radiation treatment: induction of an antitumor immune response and a protumoral response. Emphasis is placed on the molecular and cellular mechanisms involved. CONCLUSIONS: By understanding how radiation changes the balance between anti- and protumoral effects, these forces can be manipulated to optimize radiation oncology treatments.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.041
GPT teacher head0.396
Teacher spread0.355 · 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 designNot applicable
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

Citations4
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Radiation BiologySame topicEffects of Radiation ExposureFrench-language works237,207