Air pollution: An environmental factor contributing to intestinal disease
Bibliographic record
Abstract
The health impacts of air pollution have received much attention and have recently been subject to extensive study. Exposure to air pollutants such as particulate matter (PM) has been linked to lung and cardiovascular disease and increases in both hospital admissions and mortality. However, little attention has been given to the effects of air pollution on the intestine. The recent discovery of genes linked to susceptibility to inflammatory bowel diseases (IBD) explains only a fraction of the hereditary variance for these diseases. This, together with evidence of increases in incidence of IBD in the past few decades of enhanced industrialization, suggests that environmental factors could contribute to disease pathogenesis. Despite this, little research has examined the potential contribution of air pollution and its components to intestinal disease. Exposure of the bowel to air pollutants occurs via mucociliary clearance of PM from the lungs as well as ingestion via food and water sources. Gaseous pollutants may also induce systemic effects. Plausible mechanisms mediating the effects of air pollutants on the bowel could include direct effects on epithelial cells, systemic inflammation and immune activation, and modulation of the intestinal microbiota. Although there is limited epidemiologic evidence to confirm this, we suggest that a link between air pollution and intestinal disease exists and warrants further study. This link may explain, at least in part, how environmental factors impact on IBD epidemiology and disease pathogenesis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".