The Effect of Composition, Size, and Solubility on Acute Pulmonary Injury in Rats Following Exposure to Mexico City Ambient Particulate Matter Samples
Bibliographic record
Abstract
Particulate matter (PM)-associated metals can contribute to adverse cardiopulmonary effects following exposure to air pollution. The aim of this study was to investigate how variation in the composition and size of ambient PM collected from two distinct regions in Mexico City relates to toxicity differences. Male Wistar Kyoto rats (14 wk) were intratracheally instilled with chemically characterized PM10 and PM2.5 from the north and PM10 from the south of Mexico City (3 mg/kg). Both water-soluble and acid-leachable fractions contained several metals, with levels generally higher in PM10 South. The insoluble and total, but not soluble, fractions of all PM induced pulmonary damage that was indicated by significant increases in neutrophilic inflammation, and several lung injury biomarkers including total protein, albumin, lactate dehydrogenase activity, and γ-glutamyl transferase activity 24 and 72 h postexposure. PM10 North and PM2.5 North also significantly decreased levels of the antioxidant ascorbic acid. Elevation in lung mRNA biomarkers of inflammation (tumor necrosis factor [TNF]-α and macrophage inflammatory protein [MIP]-2), oxidative stress (heme oxygenase [HO]-1, lectin-like oxidized low-density lipoprotein receptor [LOX]-1, and inducibile nitric oxide synthase [iNOS]), and thrombosis (tissue factor [TF] and plasminogen activator inhibitor [PAI]-1), as well as reduced levels of fibrinolytic protein tissue plasminogen activator (tPA), further indicated pulmonary injury following PM exposure. These responses were more pronounced with PM10 South (PM10 South > PM10 North > PM2.5 North), which contained higher levels of redox-active transition metals that may have contributed to specific differences in selected lung gene markers. These findings provide evidence that surface chemistry of the PM core and not the water-soluble fraction played an important role in regulating in vivo pulmonary toxicity responses to Mexico City PM.
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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) | 0.000 | 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".