Particulate matter with a diameter of ≤2.5 μm induces and enhances bleomycin-induced pulmonary fibrosis by stimulating endoplasmic reticulum stress in rat
Bibliographic record
Abstract
This study was designed to investigate the effect of particulate matter with a diameter of ≤2.5 μm (PM2.5) on bleomycin (BLM) induced pulmonary fibrosis. Thirty-two Sprague Dawley rats were assigned into four groups (intratracheal instillation of 500 μL of PBS (control), 2 mg/kg PM2.5, 3.5 mg/kg BLM A5, and BLM plus 2.0 mg/kg PM2.5) and were fed for 14 days. All rats were sacrificed after the study. Lung tissues and bronchoalveolar lavage fluid were prepared for histological and biological analysis. We found that PM2.5 caused dose-trend pulmonary alveolitis and fibrosis. Histological scores, expression of α-SMA and Collagen I as well as contents of TNF-α and IL-6 in lung tissues were upregulated by treatment of PM2.5. PM2.5 did not change the percentage of neutrophils and macrophages. The expression of endoplasmic reticulum (ER) stress markers Chop and GRP78 was upregulated by treatment of PM2.5. In comparison with either PM2.5 or BLM treatment, BLM plus PM2.5 treatment induced higher histological scores, higher expression of α-SMA, collagen I, TNF-α, IL-6, Chop, and GRP78, with increased neutrophil counts and decreased macrophage counts. We concluded that PM2.5 instillation caused pulmonary alveolitis and fibrosis by stimulating ER stress responses in rat. PM2.5 also showed a synergistic effect on BLM-induced pulmonary fibrosis.
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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 | 0.001 |
| 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) | 0.001 | 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".