Ethyl pyruvate reduces organic dust-induced airway inflammation by targeting HMGB1-RAGE signaling
Bibliographic record
Abstract
BACKGROUND: Animal production workers are persistently exposed to organic dust and can suffer from a variety of respiratory disease symptoms and annual decline in lung function. The role of high mobility group box-1 (HMGB1) in inflammatory airway diseases is emerging. Hence, we tested a hypothesis that organic dust exposure of airway epithelial cells induces nucleocytoplasmic translocation of HMGB1 and blocking this translocation dampens organic dust-induced lung inflammation. METHODS: Rats were exposed to either ambient air or swine barn (8 h/day for either 1, 5, or 20 days) and lung tissues were processed for immunohistochemistry. Swine barn dust was collected and organic dust extract (ODE) was prepared and sterilized. Human airway epithelial cell line (BEAS-2B) was exposed to either media or organic dust extract followed by treatment with media or ethyl pyruvate (EP) or anti-HMGB1 antibody. Immunoblotting, ELISA and other assays were performed at 0 (control), 6, 24 and 48 h. Data (as mean ± SEM) was analyzed using one or two-way ANOVA followed by Bonferroni's post hoc comparison test. A p value of less than 0.05 was considered significant. RESULTS: Compared to controls, barn exposed rats showed an increase in the expression of HMGB1 in the lungs. Compared to controls, ODE exposed BEAS-2B cells showed nucleocytoplasmic translocation of HMGB1, co-localization of HMGB1 and RAGE, reactive species and pro-inflammatory cytokine production. EP treatment reduced the ODE induced nucleocytoplasmic translocation of HMGB1, HMGB1 expression in the cytoplasmic fraction, GM-CSF and IL-1β production and augmented the production of TGF-β1 and IL-10. Anti-HMGB1 treatment reduced ODE-induced NF-κB p65 expression, IL-6, ROS and RNS but augmented TGF-β1 and IL-10 levels. CONCLUSIONS: HMGB1-RAGE signaling is an attractive target to abrogate OD-induced lung inflammation.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".