Caught The Flu? Exploring the novel role of high mobility group box 1 protein in severe influenza infection
Bibliographic record
Abstract
Severe influenza infections are a common cause of acute respiratory distress syndrome (ARDS). ARDS is characterized by acute lung injury as well as pulmonary edema or “leakage,” which is caused by endothelial dysfunction and subsequent alveolar flooding from circulating blood vessels. High mobility group box 1 (HMGB1) is a protein released from lung endothelial cells that acts as a proinflammatory cytokine during bacterial and viral infections. However, the effect of HMGB1 on the endothelium during influenza viral infection is unknown. This study demonstrates that HMGB1 released from primary human microvascular lung endothelial cells (HLMECs) during influenza infection increases endothelial activation and apoptosis, while also disrupting adherens junctions between cells. Sequestering extracellular HMGB1 using the small molecule glycyrrhizin (GCZ) attenuates these effects, suggesting that HMGB1 signaling occurs in a paracrine manner. Inhibition of the Toll-like receptor (TLR) 4 pathway, a downstream effector of HMGB1, with peptide P5779 did not substantially decrease endothelial apoptosis. Therefore, HMGB1 likely elicits its effects on the endothelium in a TLR4-independent manner. These results will elucidate a partial mechanism that potentially explains ARDS symptoms seen in patients with severe influenza infections.
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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".