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Record W2037265356 · doi:10.1089/jir.2010.0158

Interferon: Current Status and Future Prospects in Cancer Therapy

2011· review· en· W2037265356 on OpenAlex
Ben X. Wang, Ramtin Rahbar, Eleanor N. Fish

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

VenueJournal of Interferon & Cytokine Research · 2011
Typereview
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsCancer stem cellStem cellCancer researchCancerImmune systemCancer cellBiologyCytotoxic T cellImmunologyGliomaBreast cancerMedicineIn vitroCell biology

Abstract

fetched live from OpenAlex

Type I interferons (IFNs) exhibit antiproliferative activity and apoptotic effects, and regulate an immune response by activating multiple cells types, including dendritic cells, cytotoxic T cells, and natural killer cells. Most recently, a report in the literature identified dysfunctional induction of a type I IFN response in cancer stem cells--specifically, breast cancer-initiating cells, implicating this defect in progression to breast cancer. Indeed, accumulating evidence suggests that cancer stem cells/cancer-initiating cells are prevalent in leukemias and solid tumors, are resistant to chemotherapy and radiation therapy, and therefore likely contribute to tumor recurrence. IFN-β treatment of human glioma xenografts leads to disruption of the vascular niche of glioma stem cells, in further support of a potential therapeutic effect of IFN treatment in limiting cancer stem cells. The implications are that restoring an IFN response, or enhancing an IFN response, may invoke a reduction, or elimination of both cancer stem cells and tumor cells. In this review, the clinical application of type I IFNs, mainly IFN-αs, will be reviewed.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.004
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 head0.209
GPT teacher head0.483
Teacher spread0.274 · 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