Effects of early life exposure to concentrated ambient particle on lung function of mice
Bibliographic record
Abstract
Introduction- Epidemiological studies have shown that air pollution affects lung health in children. Aims- To evaluate the effects of gestational and postnatal exposure to concentrated ambient particles (CAPs) derived from vehicular emissions on pulmonary inflammation and lung function in young mice. Methods- Mice (n=14/group) were continuously exposed to either filtered air (control group) or CAP (600µg/m3/day) from gestational day 5 (intrauterine exposure) to postnatal day 40 using a Harvard Ambient Particle Concentrator. At the end of exposures, mice were submitted to functional evaluation using FlexiVent small animal ventilator (SCIREQ, Montreal, PQ, Canada). Airway resistance, tissue damping and tissue elastance (Htis) were measured using the forced oscillation technique. Bronchoalveolar lavage (BAL) fluid was collected to obtain differential cell counts. Data were analyzed Student's T test. Results: There was a significant increase in the Htis (p=0.02) in the exposed group (35.64±14.70cmH2O/mL/s) when compared to the non-exposed group (26.61±5.31cmH2O/mL/s). There were no differences in BAL fluid cellularity (p=0.3). Conclusions- Our findings showed that the combined exposure during prenatal e postnatal life to particulate air pollution affects lung function. We speculate that the observed changes in tissue elastance could be related to abnormal lung development.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".