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Record W3081393016 · doi:10.1126/science.aax0701

Cross-reactivity between tumor MHC class I–restricted antigens and an enterococcal bacteriophage

2020· article· en· W3081393016 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScience · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsCentre Hospitalier de l’Université de MontréalInstitut universitaire de cardiologie et de pneumologie de Québec
FundersAgence Nationale de la Recherche
KeywordsBacteriophageImmune systemAntigenBiologyMolecular mimicryEpitopeMicrobiologyImmunityImmunologyImmunotherapyT cellVirologyGeneticsEscherichia coliGene

Abstract

fetched live from OpenAlex

Phages and cancer immunity Gut bacteria are involved in the education of T cell immune responses, and the intestinal ecosystem influences anticancer immunity. Fluckiger et al. report microbial antigens that might cross-react with antigens associated with tumor cells. They found that a type of intestinal bacteria called enterococci harbor a bacteriophage that modulates immune responses. In mouse models, administration of enterococci containing the bacteriophage boosted T cell responses after treatment with chemotherapy or programmed cell death protein 1 (PD-1) blockade. In humans, the presence of the bacteriophage was associated with improved survival after PD-1 immunotherapy. A fraction of human T cells specific for naturally processed melanoma epitopes appeared to be able to recognize microbial peptides. This “molecular mimicry” may represent cross-reactivity between tumors and microbial antigens. Science , this issue p. 936

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.826
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.002
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 head0.020
GPT teacher head0.291
Teacher spread0.271 · 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