Adiposity affects human response to inhaled organic dust
Bibliographic record
Abstract
BACKGROUND: Swine containment facilities are often highly contaminated with organic dusts that often contain varying levels of endotoxins and other microbial products. This study was performed to evaluate the effect of obesity on the inflammatory response induced by chronic or acute exposure to swine confinement buildings (SCB). METHODS: Two separate studies were performed; Study I included 36 SCB long-time workers and a control group of 35 matched male hospital workers never exposed to SCB. In Study II, 14 naïve healthy young subjects (8 overweight and 6 lean) volunteered to be acutely exposed to a SCB environment for 5 hr. Markers of sub-clinical inflammation linked to obesity (C-reactive protein (CRP), interleukin 6 (IL-6)) or to active inflammation (soluble adhesion molecules, IL-8, TNF) were measured. RESULTS: In the first study, positive correlations were found between girth circumference and serum levels of IL-6 (r = 0.57, P = 0.0003) and CRP (r = 0.62, P < 0.0001) in the control group. These correlations were however blunted or lost in the SCB workers group who showed positive correlations between girth circumference and soluble l-selectin (r = 0.34, P = 0.04), TNFalpha (r = 0.37, P = 0.03), ICAM-1 (r = 0.61, P < 0.0001). In the second study involving acute SCB exposure of naïve volunteers, no significant differences were observed between normal weight and overweight subjects for white blood cells, nasal lavage cell counts, and IL-8 levels. However, higher levels of CRP, TNF, and IL-6 were detected in overweight volunteers compared to those who were lean. CONCLUSIONS: In pig farmers (Study I), environmentally induced chronic inflammation appears to blunt the sub-clinical inflammation linked to obesity, whereas in naïve volunteers of Study II, environmentally induced acute inflammation seems to have a potentiating effect on obesity-related inflammatory markers.
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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) | 0.002 | 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".