IFN Regulatory Factor 4 Participates in the Human T Cell Lymphotropic Virus Type I-Mediated Activation of the IL-15 Receptor α Promoter
Bibliographic record
Abstract
IL-15Ralpha mRNA and protein levels are increased in human T cell lymphotropic virus type-I (HTLV-I)-associated adult T cell leukemia. Previously, we demonstrated that IL-15Ralpha expression was activated by HTLV-I Tax, in part, through the action of NF-kappaB. However, there appeared to be additional motifs within the IL-15Ralpha promoter that were responsive to HTLV-I Tax. In this study, we demonstrated that IL-15Ralpha mRNA expression was activated in human monocytes by IFN treatment, suggesting a role for IFN regulatory factors (IRFs) in IL-15Ralpha transcription. In addition, an IRF element within the Tax-responsive element of the IL-15Ralpha promoter was necessary for maximal Tax-induced activation of this promoter. Furthermore, we demonstrated that IRF-4, a transcription factor known to be elevated in HTLV-I-infected cells, activated the IL-15Ralpha promoter. Inhibition of IRF-4 action lead to reduced Tax-induced activation of the IL-15Ralpha promoter, while inhibition of both IRF-4 and NF-kappaB severely inhibited the Tax-induced activation of this promoter. These findings suggest a role for both NF-kappaB and IRF-4 in the transcriptional regulation of IL-15Ralpha by HTLV-I Tax. It is possible that the HTLV-I Tax-mediated induction of IL-15Ralpha and IL-15 may lead to an autocrine cytokine-mediated stimulatory loop leading to the proliferation of HTLV-I infected cells. This loop of proliferation may facilitate viral propagation and play a role in HTLV-I-mediated disease progression.
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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 | 0.001 |
| 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 | 0.000 |
| 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".