Inhibition of IL-12 heterodimers impairs TLR9-mediated prevention of early mouse plasmacytoma cell growth
Bibliographic record
Abstract
Introduction: Natural prevention of cancer development depends on an efficient immunosurveillance that may be modulated by environmental factors, including infections. Innate lymphoid cytotoxic cells have been shown to play a major role in this immunosurveillance. Interleukin-12 (IL-12) has been suggested to be a key factor in the activation of innate cytotoxic cells after infection, leading to the enhancement of cancer immunosurveillance. Methods: The aim of this work was to analyze in mouse experimental models by which mechanisms the interaction between infectious agent molecules and the early innate responses could enhance early inhibition of cancer growth and especially to assess the role of IL-12 by using novel antibodies specific for IL-12 heterodimers. Results: Ligation of toll-like receptor (TLR)9 by CpG-protected mice against plasmacytoma TEPC.1033.C2 cell early growth. This protection mediated by innate cytolytic cells was strictly dependent on IL-12 and partly on gamma-interferon. Moreover, the protective effect of CpG stimulation, and to a lesser extent of TLR3 and TLR7/8, and the role of IL-12 in this protection were confirmed in a model of early mesothelioma AB1 cell growth. Discussion: These results suggest that modulation of the mouse immune microenvironment by ligation of innate receptors deeply modifies the efficiency of cancer immunosurveillance through the secretion of IL-12, which may at least partly explain the inhibitory effect of previous infections on the prevalence of some cancers.
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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) | 0.001 | 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) | 0.003 | 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".