Sec22b Regulates Inflammatory Responses by Controlling the Nuclear Translocation of NF-κB and the Secretion of Inflammatory Mediators
Bibliographic record
Abstract
-ethylmaleimide-sensitive factor attachment protein receptors (SNAREs) regulate the vesicle transport machinery in phagocytic cells. Within the secretory pathway, Sec22b is an endoplasmic reticulum-Golgi intermediate compartment (ERGIC)-resident SNARE that controls phagosome maturation and function in macrophages and dendritic cells. The secretory pathway controls the release of cytokines and may also impact the secretion of NO, which is synthesized by the Golgi-active inducible NO synthase (iNOS). Whether ERGIC SNARE Sec22b controls NO and cytokine secretion is unknown. Using murine bone marrow-derived dendritic cells, we demonstrated that inducible NO synthase colocalizes with ERGIC/Golgi markers, notably Sec22b and its partner syntaxin 5, in the cytoplasm and at the phagosome. Pharmacological blockade of the secretory pathway hindered NO and cytokine release, and inhibited NF-κB translocation to the nucleus. Importantly, RNA interference-mediated silencing of Sec22b revealed that NO and cytokine production were abrogated at the protein and mRNA levels. This correlated with reduced nuclear translocation of NF-κB. We also found that Sec22b co-occurs with NF-κB in both the cytoplasm and nucleus, pointing to a role for this SNARE in the shuttling of NF-κB. Collectively, our data unveiled a novel function for the ERGIC/Golgi, and its resident SNARE Sec22b, in the production and release of inflammatory mediators.
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 | 0.001 | 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".