The Unfolded Protein Response Sensor IRE1 Regulates Activation of In Vitro Differentiated Type 1 Conventional DCs with Viral Stimuli
Bibliographic record
Abstract
Type 1 conventional dendritic cells (cDC1s) are leukocytes competent to coordinate antiviral immunity, and thus, the intracellular mechanisms controlling cDC1 function are a matter of intense research. The unfolded protein response (UPR) sensor IRE1 and its associated transcription factor XBP1s control relevant functional aspects in cDC1s including antigen cross-presentation and survival. However, most studies connecting IRE1 and cDC1 function are undertaken in vivo. Thus, the aim of this work is to elucidate whether IRE1 RNase activity can also be modeled in cDC1s differentiated in vitro and reveal the functional consequences of such activation in cells stimulated with viral components. Our data show that cultures of optimally differentiated cDC1s recapitulate several features of IRE1 activation noticed in in vivo counterparts and identify the viral analog Poly(I:C) as a potent UPR inducer in the lineage. In vitro differentiated cDC1s display constitutive IRE1 RNase activity and hyperactivate IRE1 RNase upon genetic deletion of XBP1s, which regulates production of the proinflammatory cytokines IL-12p40, TNF-α and IL-6, Ifna and Ifnb upon Poly(I:C) stimulation. Our results show that a strict regulation of the IRE1/XBP1s axis regulates cDC1 activation to viral agonists, expanding the scope of this UPR branch in potential DC-based therapies.
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 | 0.000 |
| 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".