TLR4 dependent lung inflammation following exposure to swine barn air
Bibliographic record
Abstract
Swine farmers repeatedly exposed to the endotoxin‐rich barn air report higher incidence of respiratory diseases. However, the in situ lung responses and the mechanisms involved are unclear. We hypothesized that, lung inflammation induced following barn air exposure is TLR4 dependent. We exposed C3HeB/FeJ (intact TLR4) and C3H/HeJ (natural mutation in TLR4 gene) either to the barn air (8 hours/day for 1 or 5 or 20 days) or ambient air. After 5 days exposure, there was an interruption of two days to mimic occupational exposure pattern of swine barn workers. Following barn or ambient air exposure, airway hyper‐responsiveness (AHR) to methacholine and bronchoalveolar lavage fluid (BALF) for inflammatory cell influx was analyzed. Both C3HeB/FeJ and C3H/HeJ mice were similar in their AHR (P= 0.455) following exposure and the combined data (C3HeB/FeJ and C3H/HeJ) showed significant barn air exposure effect on AHR compared to the controls (P= 0.00). Five day exposure induced higher AHR compared to control, 1 and 20 day exposure (P < 0.01) while control and 1 day exposed mice did not differ (P > 0.05). Increased AHR is similar in both the strains of mice indicating that it is independent of TLR4. BALF total leukocytes were higher only in 1‐day exposed C3HeB/FeJ mice compared to controls and 20 day exposed C3HeB/FeJ and C3H/HeJ mice. Increased BALF leukocytes in 1 day exposed C3HeB/FeJ mice were characterized by increased neutrophils, macrophages and lymphocytes. We conclude that swine barn air induced lung inflammation but not AHR, is regulated via TLR4 (Lung Association of Saskatchewan and PHARE graduate training program).
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".