High-mobility group box 1 promotes extracellular matrix synthesis and wound repair in human bronchial epithelial cells
Bibliographic record
Abstract
High mobility group box 1 (HMGB1) is a damage-associated molecular pattern (DAMP) protein that binds Toll-like receptors (e.g., TLR4) and the receptor for advanced glycated end products (RAGE). The direct effects of HMGB1 on airway structural cells are not fully known. As epithelial cell responses are fundamental drivers of asthma, including abnormal repair-restitution linked to changes in extracellular matrix (ECM) synthesis, we tested the hypothesis that HMGB1 promotes bronchial epithelial cell wound repair via TLR4 and/or RAGE signaling that regulates ECM (fibronectin and the γ2-chain of laminin-5) and integrin protein abundance. To assess impact of HMGB1 we used molecular and pharmacological inhibitors of RAGE or TLR4 signaling in scratch wound, immunofluorescence, and immunoblotting assays to assess wound repair, ECM synthesis, and phosphorylation of intracellular signaling. HMGB1 increased wound closure, and this effect was attenuated by blocking RAGE and TLR4 signaling. HMGB1-induced fibronectin and laminin-5 (γ2 chain) was diminished by blocking RAGE and/or blunting TLR4 signaling. Similarly, induction of α3-integrin receptor for fibronectin and laminin-5 was also diminished by blocking TLR4 signaling and RAGE. Lastly, rapid and/or sustained phosphorylation of SMAD2, ERK1/2, and JNK signaling modulated HMGB1-induced wound closure. Our findings suggest a role for HMGB1 in human airway epithelial cell repair and restitution via multiple pathways mediated by TLR4 and RAGE that underpin increased ECM synthesis and modulation of cell-matrix adhesion.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".