Disruption of NF-κB Signaling Reveals a Novel Role for NF-κB in the Regulation of TNF-Related Apoptosis-Inducing Ligand Expression
Bibliographic record
Abstract
The NF-kappaB family of transcription factors functions broadly in the host control of immunoregulatory gene expression, inflammation, and apoptosis. Using Jurkat T cells engineered to inducibly express a transdominant repressor of IkappaBalpha, we examined the role of NF-kappaB in the regulation of cytokine and apoptotic gene expression. In this T cell model, as well as in primary T lymphocytes, expression of TNF-related apoptosis-inducing ligand (TRAIL) apoptotic signaling protein was dramatically down-regulated by inhibition of NF-kappaB binding activity. TRAIL acts through membrane death receptors to induce apoptosis of activated T lymphocytes and can be up-regulated by a variety of physiological and pharmacological inducers. However, regulation of TRAIL gene expression has not been defined. Treatment with TCR mimetics (PMA/ionomycin, PHA, and anti-CD3/CD28 Abs) resulted in a rapid increase in the expression of TRAIL mRNA and cell surface TRAIL protein. Induction of the transdominant repressor of IkappaBalpha dramatically down-regulated surface expression of TRAIL, indicating an essential role for NF-kappaB in the regulation of TRAIL. The induced expression of TRAIL was linked to a c-Rel binding site in the proximal TRAIL promoter at position -256 to -265; mutation of this site or an adjacent kappaB site resulted in a complete loss of the inducibility of the TRAIL promoter. The regulation of TRAIL expression by NF-kappaB may represent a general mechanism that contributes to the control of TRAIL-mediated apoptosis in T lymphocytes.
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.
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) | 0.001 | 0.000 |
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.
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".