LSC Abstract – High mobility group box 1 modulates lung innate immunity by promoting wound healing and cytokine release in human bronchial epithelial cells
Bibliographic record
Abstract
Airway pathogens damage epithelium integrity and stimulate toll like receptors (TLRs) on bronchial epithelial cells to release inflammatory mediators. In addition, damage associated molecular pattern (DAMP) proteins like high mobility group box 1 (HMGB1) are released and bind to TLR4. We investigated whether exogenous HMGB1 and TLR4 signaling promote wound repair, cytokine release and mucocilliary markers in human bronchial epithelial (HBE) cells. <b>Method:</b> Using air liquid interface (ALI) bronchial epithelial cell cultures, we assessed impact of HMGB1 on cytokine release (ELISA) and mucocilliary markers (RT-PCR) in the presence or absence of a TLR4 signaling inhibitor (CLI-095). We assessed HMGB1-TLR4 axis on bronchial epithelial wound healing by phase contrast microscopy using a scratch wound assay and tested whether this was coupled to extracellular matrix (ECM) synthesis by immunocytochemistry. <b>Result:</b> HMGB1 increased wound closure by ∼30% and was linked to accumulation of ECM proteins: fibronectin, γ2 chain of laminin-5 and α3 integrin. Wound closure and ECM expression was diminished by blunting TLR4 and inhibiting MAPK signaling. Furthermore, HMGB1 induced IL-8 and IL-1β secretion and increased MUC5AC mRNA expression. These effects on cytokine and MUC5AC mRNA expression were diminished by concomitant pharmacological inhibition of TLR4, ERK1/2, p38 and JNK signaling. <b>Conclusion:</b> HMGB1-TLR4 axis couples to downstream MAPK signaling to modulate wound repair, cytokine release and mucocilliary markers of HBE cells. These responses underpin bronchial epithelial cell function as a key player in lung innate immunity.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".