Metal rich particulate matter impairs acetylcholine-mediated vasorelaxation of microvessels in mice
Bibliographic record
Abstract
BACKGROUND: Exposure to PM2.5 (particulate matter<2.5 μm) has been associated with changes in endothelial function. PM2.5 was collected from two Chinese cities, Jinchang (JC) and Zhangye (ZH), both with similar PM2.5 concentrations. However, JC had levels of nickel (Ni), selenium (Se), copper (Cu), and arsenic (As) that were 76, 25, 17, and 7 fold higher than that measured in ZH, respectively. We used this unique PM sample to delineate the chemical components that drive pulmonary and systemic effects and explore the mechanism(s) by which vascular dysfunction is caused. METHODS: Male FVB/N mice received oropharyngeal aspiration of water or PM2.5 from JC, ZH or ZH spiked with one of the following elements at the same concentrations found in the JC PM (Ni=4.76; As=2.36; Se=0.24; Cu=2.43 μg/mg) followed by evaluation of markers of pulmonary and systemic inflammation. Mesenteric arteries were isolated for gene expression or functional response to various agonists (Phenylephrine, Acetylcholine, and Sodium Nitroprusside) and inhibitors (L-NAME, Apocynin, and VAS2870) ex vivo. RESULTS: Protein and total cell counts from lung lavage revealed significant pulmonary inflammation from ZH (p<0.01) and JC and ZH+NiSO4 (p<0.001) as compared to control and a significant decrease in mesenteric artery relaxation (p<0.001) and this decrease is blunted in the presence of NADPH oxidase inhibitors. Significant increases in gene expression (TNF-α, IL-6, Nos3; p<0.01; NOX4; p<0.05) were observed in JC and ZH+NiSO4, as well as significantly higher concentrations of VEGF and IL-10 (p<0.01, p<0.001; respectively). CONCLUSIONS: Our results indicate that the specific toxicity observed in PM from JC is likely due to the nickel component in the PM. Further, since VAS2870 was the most successful inhibitor to return vessels to baseline relaxation values, NADPH Oxidase is implicated as the primary source of PM-induced O2•-.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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".