The p38 Mitogen-activated Kinase Pathway Regulates the Human Interleukin-10 Promoter via the Activation of Sp1 Transcription Factor in Lipopolysaccharide-stimulated Human Macrophages
Bibliographic record
Abstract
Interleukin-10 (IL-10), a pleiotropic cytokine that inhibits inflammatory and cell-mediated immune responses, is produced by a wide variety of cell types including T and B cells and monocytes/macrophages. Regulation of pro- and anti-inflammatory cytokines has been suggested to involve distinct signaling pathways. In this study, we investigated the regulation of the human IL-10 (hIL-10) promoter in the human monocytic cell line THP-1 following activation with lipopolysaccharide (LPS). Analysis of hIL-10 promoter sequences revealed that DNA sequences located between base pairs -652 and -571 are necessary for IL-10 transcription. A computer analysis of the promoter sequence between base pairs -652 and -571 revealed the existence of consensus sequences for Sp1, PEA1, YY1, and Epstein-Barr virus-specific nuclear antigen-2 (EBNA-2)-like transcription factors. THP-1 cells transfected with a plasmid containing mutant Sp1 abrogated the promoter activity, whereas plasmids containing the sequences for PEA1, YY1, and EBNA-2-like transcription factors did not influence hIL-10 promoter activity. To understand the events upstream of Sp1 activation, we investigated the role of p38 and extracellular signal-regulated kinase mitogen-activated protein kinases by using their specific inhibitors. SB202190 and SB203580, the p38-specific inhibitors, inhibited LPS-induced IL-10 production. In contrast, PD98059, a specific inhibitor of extracellular signal-regulated kinase kinases, failed to modulate IL-10 production. Furthermore, SB203580 inhibited LPS-induced activation of Sp1, as well as the promoter activity in cells transfected with a plasmid containing the Sp1 consensus sequence. These results suggest that p38 mitogen-activated protein kinase regulates LPS-induced activation of Sp1, which in turn regulates transcription of the hIL-10 gene.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".