ER stress and its regulator X‐box‐binding protein‐1 enhance polyIC‐induced innate immune response in dendritic cells
Bibliographic record
Abstract
Multiple physiological and pathological conditions interfere with the function of the endoplasmic reticulum (ER). However, much remains unknown regarding the impact of ER stress on inflammatory responses in dendritic cells (DCs) upon the recognition of pathogen molecules. We show that ER stress greatly potentiates the expression of inflammatory cytokines and IFN-β in murine DCs stimulated by polyIC, a synthetic mimic of virus dsRNA. Both toll-like receptor 3 and melanoma differentiation-associated gene-5 are involved in the enhanced IFN-β production, which is associated with increased activation of NF-κB and IRF3 signaling as well as the splicing of X-box-binding protein-1 (XBP-1), an important regulator involved in ER stress response. Surprisingly, silencing of XBP-1 reduces polyIC-stimulated IFN-β expression in the presence or absence of ER stress, indicating that XBP-1 may be essential for polyIC signaling and ER stress-amplified IFN-β production. Overexpression of a spliced form of XBP-1 (XBP-1s) synergistically augments polyIC-induced inflammatory response. For the first time, we show that XBP-1s overexpression-enhanced IFN-β production in DCs markedly suppresses vesicular stomatitis virus infection, revealing a previously unrecognized role for XBP-1 in an antiviral response. Our findings suggest that evolutionarily conserved ER stress response and XBP-1 may function collaboratively with innate immunity to maintain cellular homeostasis.
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 | 0.000 | 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".