The Human Bone Marrow Response to Acute Air Pollution Caused by Forest Fires
Bibliographic record
Abstract
Atmospheric pollution increases cardiopulmonary morbidity and mortality by unexplained mechanisms. Phagocytosis of fine particles (PM(10)) by rabbit alveolar macrophages elevates white blood cells (WBC) by releasing precursors from the bone marrow and this could contribute to the pathogenesis of cardiopulmonary disease. The present study examined the association between acute air pollution caused by biomass burning and peripheral WBC counts in humans. Serial measurements of the WBC count made during the 1997 Southeast Asian Smoke-haze (Sep 29, Oct 27) were compared with a period after the haze cleared (Nov 21, Dec 5) using peripheral blood PMN band cells to monitor marrow release. The results showed that indices of atmospheric pollution were significantly associated with elevated band neutrophil counts expressed as a percentage of total polymorphonuclear leukocytes (PMN), with maximal association on zero and 1 lag day for PM(10) and 3, and 4 lag days for SO(2) (p value < 0.000). We conclude that atmospheric pollution caused by biomass burning is associated with elevated circulating band cell counts in humans because of the increased release of PMN precursors from the marrow. We speculate that this response contributes to the pathogenesis of the cardiorespiratory morbidity associated with acute air pollution.
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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".