VEGF Requires the Receptor NRP-1 To Inhibit Lipopolysaccharide-Dependent Dendritic Cell Maturation
Bibliographic record
Abstract
To stimulate a productive T cell response, dendritic cells (DC) must undergo maturation characterized by heightened cell surface expression of MHC and costimulatory molecules as well as cytokine production. Conversely, the inhibition of DC maturation is a central mechanism of immune tolerance. The control of the DC maturation process relies on the integration of several cellular stimulatory or inhibitory signals. The soluble factors and their receptors controlling this central aspect of DC biology are incompletely characterized. We show that murine bone marrow-derived DC (BMDC) maturation induced by LPS, as opposed to polyinosinic:polycytidylic acid or cytosine-phosphate-guanine, is robustly inhibited by vascular endothelial growth factor (VEGF), a previously identified immunosuppressive cytokine. Using BMDC from wild type and conditional knockout mice, we show that neuropilin-1 (NRP-1), a known receptor of VEGF, is necessary to suppress LPS-dependent BMDC maturation. The absence of NRP-1 had no ostensible effects on the biology of BMDC in the absence of VEGF. However, NRP-1-deficient BMDC remained completely insensitive to the VEGF-dependent inhibition of BMDC maturation in culture. In the presence of VEGF, NRP-1 directly interacted with the LPS receptor TLR4 and suppressed downstream signaling through ERK and NF-κβ, resulting in a sharp inhibition of MHC class II and costimulatory molecules (CD40, CD86) expression as well as proinflammatory cytokine production. Consequently, we identify NRP-1 as a target to optimize DC maturation within environments that are rich in VEGF, such as tumors.
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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 | 0.001 |
| 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".