Identificaiton and characterization of the antitumor suppressor activity of interferon regulatory factor 3 (IRF-3) in B16 melanoma tumor model
Bibliographic record
Abstract
Delivery of transcription factor to cancer cells to reprogram gene expression may represent a novel strategy to augment the production of immune stimulatory cytokines and trigger a more potent antitumor response. In this study, we used a syngeneic mouse tumor model system involving the poorly immunogenic murine B16 tumor to evaluate whether delivery of the interferon regulatory factor 3 (IRF-3) can be used as an immunomodulator. The low immunogenicity of B16 melanoma cells may be due to their deficient cytokine expression, as well as their inefficient MHC-restricted epitope presentation. Gene-modified B16 melanoma cells were selected for their ability to express and to activate the IRF-3 protein. When injected into C57BL/6 mice, tumor growth was inhibited and tumors that developed from these mice had significant infiltration of inflammatory cells. Our observations demonstrated that gene transfer of IRF-3 into B16 melanoma could mediate important antitumor response by restoring both the deficient cytokine profile and the MHC class I protein expression.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".