Hydrogen Peroxide Induces Murine Macrophage Chemokine Gene Transcription Via Extracellular Signal-Regulated Kinase- and Cyclic Adenosine 5′-Monophosphate (cAMP)-Dependent Pathways: Involvement of NF-κB, Activator Protein 1, and cAMP Response Element Binding Protein
Bibliographic record
Abstract
Hydrogen peroxide (H(2)O(2)) has been shown to act as a second messenger that activates chemokine expression. In the present study, we investigated the mechanisms underlying this cellular regulation in the murine macrophage cell line B10R. We report that H(2)O(2) increases mRNA expression of various chemokines, macrophage-inflammatory protein (MIP)-1alpha/CC chemokine ligand (CCL)3, MIP-1beta/CCL4, MIP-2/CXC chemokine ligand 2, and monocyte chemoattractant protein-1/CCL2, by activating the extracellular signal-regulated kinase (ERK) pathway and the nuclear translocation of the transcription factors NF-kappaB, AP-1, and CREB. Blockage of the ERK pathway with specific inhibitors against mitogen-activated protein kinase kinase 1/2 and ERK1/ERK2 completely abolished both the H(2)O(2)-mediated chemokine up-regulation and the activation of all NF studied. Similarly, selective inhibition of cAMP and NF-kappaB strongly down-regulated the induction of all chemokine transcripts as well as CREB and NF-kappaB activation, respectively. Of interest, we detected a significant decrease of NF-kappaB, AP-1, and CREB DNA binding activities by reciprocal competition for these binding sites when either specific cold oligonucleotides (NF-kappaB, AP-1, and CREB) or Abs against various transcription factor subunits (p50, p65, c-Fos, Jun B, c-Jun, and CREB-1) were added. These findings indicate that cooperation between ERK- and cAMP-dependent pathways seems to be required to achieve the formation of an essential transcriptional factor complex for maximal H(2)O(2)-dependent chemokine modulation. Finally, experiments performed with actinomycin D suggest that H(2)O(2)-mediated MIP-1beta mRNA up-regulation results from transcriptional control, whereas that of MIP-1alpha, MIP-2, and monocyte chemoattractant protein-1 is due to both gene transcription activation and mRNA posttranscriptional stabilization.
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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 | 0.000 |
| 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".