Proinflammatory tachykinins that signal through the neurokinin 1 receptor promote survival of dendritic cells and potent cellular immunity
Bibliographic record
Abstract
Dendritic cells (DCs) are the preferred targets for immunotherapy protocols focused on stimulation of cellular immune responses. However, regardless of initial promising results, ex vivo generated DCs do not always promote immune-stimulatory responses. The outcome of DC-dependent immunity is regulated by proinflammatory cytokines and neuropeptides. Proinflammatory neuropeptides of the tachykinin family, including substance P (SP) and hemokinin-1 (HK-1), bind the neurokinin 1 receptor (NK1R) and promote stimulatory immune responses. Nevertheless, the ability of pro-inflammatory tachykinins to affect the immune functions of DCs remains elusive. In the present work, we demonstrate that mouse bone marrow-derived DCs (BMDCs) generated in the presence of granulocyte macrophage-colony stimulating factor (GM-CSF) and interleukin-4 (IL-4), express functional NK1R. Signaling via NK1R with SP, HK-1, or the synthetic agonist [Sar(9)Met(O(2))(11)]-SP rescues DCs from apoptosis induced by deprivation of GM-CSF and IL-4. Mechanistic analysis demonstrates that NK1R agonistic binding promotes DC survival via PI3K-Akt signaling cascade. In adoptive transfer experiments, NK1R-signaled BMDCs loaded with Ag exhibit increased longevity in draining lymph nodes, resulting in enhanced and prolonged effector cellular immunity. Our results contribute to the understanding of the interactions between the immune and nervous systems that control DC function and present a novel approach for ex vivo-generation of potent immune-stimulatory DCs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".