Lysosomal rupture induced by structurally distinct chitosans either promotes a type 1 IFN response or activates the inflammasome in macrophages
Bibliographic record
Abstract
Chitosan is a family of glucosamine and N-acetyl glucosamine polysaccharides with poorly understood immune modulating properties. Here, functional U937 macrophage responses were analyzed in response to a novel library of twenty chitosans with controlled degree of deacetylation (DDA, 60–98%), molecular weight (1 to >100 kDa), and acetylation pattern (block vs. random). Specific chitosan preparations (10 or 190 kDa 80% block DDA and 3, 5, or 10 kDa 98% DDA) either induced macrophages to release CXCL10 and IL-1ra at 5–50 μg/mL, or activated the inflammasome to release IL-1β and PGE2 at 50–150 μg/mL. Chitosan induction of these factors required lysosomal acidification. CXCL10 production was preceded by lysosomal rupture as shown by time-dependent co-localization of galectin-3 and chitosan and slowed autophagy flux, and specifically depended on IFN-β paracrine activity and STAT-2 activation that could be suppressed by PGE2. Chitosan induced a type I IFN paracrine response or inflammasome response depending on the extent of lysosomal rupture and cytosolic foreign body invasion. This study identifies the structural motifs that lead to chitosan-driven cytokine responses in macrophages and indicates that lysosomal rupture is a key mechanism that determines the endogenous release of either IL-1ra or IL-1β.
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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 | 0.000 |
| 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".