Lung inflammation following a single exposure to swine barn air
Bibliographic record
Abstract
BACKGROUND: Exposure to swine barn air is an occupational hazard. Barn workers following an eight-hour work shift develop many signs of lung dysfunction including lung inflammation. However, the in situ cellular and molecular mechanisms responsible for lung dysfunction induced following exposure to the barn air remain largely unknown. Specifically, the recruitment and role of pulmonary intravascular monocytes/macrophages (PIMMs), which increase host susceptibility for acute lung inflammation, remain unknown in barn air induced lung inflammation. We hypothesized that barn exposure induces recruitment of PIMMs and increases susceptibility for acute lung inflammation with a secondary challenge. METHODS: Sprague-Dawley rats were exposed either to the barn or ambient air for eight hours and were euthanized at various time intervals to collect blood, broncho-alveolar lavage fluid (BALF) and lung tissue. Subsequently, following an eight hour barn or ambient air exposure, rats were challenged either with Escherichia coli (E. coli) lipopolysaccharide (LPS) or saline and euthanized 6 hours post-LPS or saline treatment. We used ANOVA (P < 0.05 means significant) to compare group differences. RESULTS: An eight-hour exposure to barn air induced acute lung inflammation with recruitment of granulocytes and PIMMs. Granulocyte and PIMM numbers peaked at one and 48 hour post-exposure, respectively.Secondary challenge with E. coli LPS at 48 hour following barn exposure resulted in intense lung inflammation, greater numbers of granulocytes, increased number of cells positive for TNF-alpha and decreased amounts of TGF-beta2 in lung tissues. We also localized TNF-alpha, IL-1beta and TGF-beta2 in PIMMs. CONCLUSION: A single exposure to barn air induces lung inflammation with recruitment of PIMMs and granulocytes. Recruited PIMMs may be linked to more robust lung inflammation in barn-exposed rats exposed to LPS. These data may have implications of workers exposed to the barn air who may encounter secondary microbial challenge.
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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 | 0.001 | 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".