Interferon Receptor Signaling in Malignancy: A Network of Cellular Pathways Defining Biological Outcomes
Bibliographic record
Abstract
IFNs are cytokines with important antiproliferative activity and exhibit key roles in immune surveillance against malignancies. Early work initiated over three decades ago led to the discovery of IFN receptor activated Jak-Stat pathways and provided important insights into mechanisms for transcriptional activation of IFN-stimulated genes (ISG) that mediate IFN biologic responses. Since then, additional evidence has established critical roles for other receptor-activated signaling pathways in the induction of IFN activities. These include MAPK pathways, mTOR cascades, and PKC pathways. In addition, specific miRNAs appear to play a significant role in the regulation of IFN signaling responses. This review focuses on the emerging evidence for a model in which IFNs share signaling elements and pathways with growth factors and tumorigenic signals but engage them in a distinctive manner to mediate antiproliferative and antiviral responses.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".