Air pollution and retained particles in the lung.
Bibliographic record
Abstract
Epidemiologic evidence associates particulate air pollution with cardiopulmonary morbidity and mortality. The biological mechanisms underlying these associations and the relationship between ambient levels and retained particles in the lung remain uncertain. We examined the parenchymal particle content of 11 autopsy lungs from never-smoking female residents of Mexico City, a region with high ambient particle levels [3-year mean PM(10) (particulate matter < or = 10 microm in aerodynamic diameter)= 66 microg/m(3)], and 11 control residents of Vancouver, British Columbia, Canada, a region with relatively low levels (3-year mean PM(10) = 14 microg/m(3). Autopsy lungs were dissolved in bleach and particles were identified and counted by analytical electron microscopy. Total particle concentrations in the Mexico City lungs were significantly higher [geometric mean = 2,055 (geometric SD = 3.9) x 10(6) particles/g dry lung vs. 279 (1.8) x 10(6) particles/g dry lung] than in lungs from Vancouver residents. Lungs from Mexico City contained numerous chain-aggregated masses of ultrafine carbonaceous spheres, some of which contained sulfur, and aggregates of ultrafine aluminum silicate. These aggregates made up an average of 25% of the total particles by count in the lungs from Mexico City, but were only rarely seen in lungs from Vancouver. These observations indicate for the first time that residence in a region with high levels of ambient particles results in pulmonary retention of large quantities of fine and ultrafine particle aggregates, some of which appear to be combustion products.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.001 | 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 teacher head, 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".