Endotoxin-induced translocation of interleukin-6 from lungs to the systemic circulation
Bibliographic record
Abstract
It is widely postulated that systemic inflammation related to lung infections is largely caused by cytokine translocation from the lungs into the systemic circulation but there is a paucity of animal models to evaluate this hypothesis. In this proof-of-concept study, we developed a murine model to determine whether interleukin (IL)-6, a primary inflammatory cytokine, translocates following airway exposure to endotoxin. We collected central venous blood from the right atrium and arterial blood from the aorta simultaneously at 4 h and 24 h following intratracheal exposure to endotoxin (25 microg) and measured IL-6 in the serum and broncho-alveolar lavage (BAL) fluid (n = 33 mice). We repeated the experiment following 3 d of treatment with dexamethasone (n = 31 mice). Without stimulation, there was no significant arteriovenous gradient (3 pg/ml with interquartile range [IQR] of 3-5 pg/ml in arterial versus 18 pg/ml with IQR of 8-24 pg/ml in venous serum; P = 0.86). A significant arteriovenous difference was observed by 4 h post-exposure to endotoxin (2813 pg/ml with IQR of 1578-4316 pg/ml in arterial versus 1282 pg/ml with IQR of 778-2699 pg/ml in venous serum; P50.0001). The rise in the BAL IL-6 levels correlated with the increases in the arterial serum levels (P50.0001). Administration of intraperitoneal dexamethasone for 3 d attenuated the increased arteriovenous gradient. This murine model facilitates the estimation of cytokine translocation across the lungs and evaluation of compounds to modulate this gradient.
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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) | 0.001 | 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".