Norepinephrine Inhibits Macrophage Migration by Decreasing CCR2 Expression
Bibliographic record
Abstract
Increased incidences of infectious and septic complications during post-burn courses represent the main contributor to burn injury mortality. Sustained increases in catecholamine levels, especially norepinephrine (NE), contribute to immune disturbances in severely burned patients. The precise mechanisms underlying NE-mediated immunoregulation are not fully understood. Here we hypothesize that persistently elevated NE levels are associated with immunodysfunctions. We examined the effects of NE on the phenotype and functions of bone marrow-derived macrophages (BMMs). Whole mouse bone marrow cells were treated in vitro with 40 ng/mL of M-CSF and with 1 x 10(-6) M or 1 x 10(-8) M of NE or without NE for 7 days; cells were collected and stained with antibodies for CD11b, F4/80, MHC II and the inflammatory CC chemokine receptor 2 (CCR2). We found 1 x 10(-6) M of NE inhibited MHC II and CCR2 expression on CD11b(+)/F4/80(+) BMM cells. It also inhibited BMM proliferation by inhibiting CSF-1R expression. On the contrary, 1 x 10(-8) M of NE slightly increased both MHC II and CCR2 expression on CD11b(+)/F4/80(+) BMM cells but inhibited CD11b(+)/F4/80(+) BMM proliferation. MCP-1 based migration assay showed that the migration of 1 x 10(-6) M of NE-treated BMM toward MCP-1 was significantly decreased compared to BMM without NE treatment. Both 1 x 10(-8) M and 1 x 10(-6) M of NE enhanced TNF-α production and phagocytosis of FITC-Dextran. Intracellular staining of transcriptional factor MafB showed that 1 x 10(-6) M of NE treatment enhanced its expression, whereas 1 x 10(-8) M of NE decreased expression. Stimulation with LPS in the last 24-hours of BMM culture further decreased CCR2 and MHC II expression of these BMM, suggesting the synergistic effect of LPS and NE on macrophage. Our results demonstrate that NE regulates macrophage differentiation, proliferation and function, and may play a critical role in the dysfunctional immune response post-burn.
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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) | 0.000 | 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 | 0.000 |
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".