The Effect of Repeated Exposure to Particulate Air Pollution (PM10) on the Bone Marrow
Bibliographic record
Abstract
Studies have shown that exposure to ambient particulate matter is related to an increased cardiopulmonary morbidity and mortality. The present study was designed to measure the effect of repeated exposure to urban air particles (PM10) on the rate of production and release of polymorphonuclear leukocytes (PMN) from the bone marrow into the peripheral blood. Rabbits exposed to PM10 (5 mg) twice a week for 3 wk, were given a bolus of 5'-bromo-2'-deoxyuridine (BrdU) to label dividing cells in the marrow that allows us to calculate the transit time of PMN in the bone marrow mitotic and postmitotic pools. The PM10 exposure (n = 8) causes a persistent increase in circulating band cells (p < 0.05) and a shortening of the transit time of PMN through the postmitotic pool in the marrow (64.4 +/- 2.2 h to 56.3 +/- 2.2 h, p < 0.05) if compared with vehicle-exposed control subjects (n = 6). PM10 exposure increases the bone marrow pool of PMN particularly the mitotic pool of PMN (p < 0.05). The PM10 were distributed diffusely in the lung and caused a mild mononuclear inflammation. The percentage of alveolar macrophages containing PM10 correlated significantly with the bone marrow PMN pool size (total pool r2 = 0.56, p < 0.012, mitotic pool r2 = 0.61, p < 0.007) and the transit time of PMN through the postmitotic pool (r2 = -0.42, p < 0.043). We conclude that repeated exposure to PM10 stimulates the bone marrow to increase the production of PMN in the marrow and accelerate the release of more immature PMN into the circulation. The magnitude of these changes was related to the amount of particles phagocytosed by alveolar macrophages.
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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) | 0.001 | 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 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".