Exposure to inhaled nickel nanoparticles causes a reduction in number and function of bone marrow endothelial progenitor cells
Bibliographic record
Abstract
INTRODUCTION: Particulate matter (PM), specifically nickel (Ni) found on or in PM, has been associated with an increased risk of mortality in human population studies and significant increases in vascular inflammation, generation of reactive oxygen species, altered vasomotor tone, and potentiated atherosclerosis in murine exposures. Recently, murine inhalation of Ni nanoparticles have been shown to cause pulmonary inflammation that affects cardiovascular tissue and potentiates atherosclerosis. These adverse cardiovascular outcomes may be due to the effects of Ni on endothelial progenitor cells (EPCs), endogenous semi-pluripotent stem cells that aid in endothelial repair. Thus, we hypothesize that Ni nanoparticle exposures decrease cell count and cause impairments in function that may ultimately have significant effects on various cardiovascular diseases, such as, atherosclerosis. METHODS: Experiments involving inhaled Ni nanoparticle exposures (2 days/5 h/day at ∼1200 µg/m(3), 3 days/5 h/day at ∼700 µg/m(3), and 5 days/5 h/day at ∼100 µg/m(3)), were performed in order to quantify bone marrow resident EPCs using flow cytometry in C57BL/6 mice. Plasma levels of human stromal cell-derived factor 1α (SDF-1α) and vascular endothelial growth factor (VEGF) were assessed by enzyme-linked immunosorbent assay and in vitro functional assessments of cultured EPCs were conducted. RESULTS AND CONCLUSIONS: Significant EPC count differences between exposure and control groups for Ni nanoparticle exposures were observed. Differences in EPC tube formation and chemotaxis were also observed for the Ni nanoparticle exposed group. Plasma VEGF and SDF-1α differences were not statistically significant. In conclusion, this study shows that inhalation of Ni nanoparticles results in functionally impaired EPCs and reduced number in the bone marrow, which may lead to enhanced progression of atherosclerosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".