Hepatic and Pulmonary Toxicogenomic Profiles in Mice Intratracheally Instilled With Carbon Black Nanoparticles Reveal Pulmonary Inflammation, Acute Phase Response, and Alterations in Lipid Homeostasis
Bibliographic record
Abstract
Global pulmonary and hepatic messenger RNA profiles in adult female C57BL/6 mice intratracheally instilled with carbon black nanoparticles (NPs) (Printex 90) were analyzed to identify biological perturbations underlying systemic responses to NP exposure. Tissue gene expression changes were profiled 1, 3, and 28 days following exposure to 0.018, 0.054, and 0.162 mg Printex 90 alongside controls. Pulmonary response was marked by increased expression of inflammatory markers and acute phase response (APR) genes that persisted to day 28 at the highest exposure dose. Genes in the 3-hydroxy-3-methylglutaryl-Coenzyme A (HMG-CoA) reductase pathway were increased, and those involved in cholesterol efflux were decreased at least at the highest dose on days 1 and 3. Hepatic responses mainly consisted of the HMG-CoA reductase pathway on days 1 (high dose) and 28 (all doses). Protein analysis in tissues and plasma of 0.162 mg Printex 90-exposed mice relative to control revealed an increase in plasma serum amyloid A on days 1 and 28 (p < 0.05), decreases in plasma high-density lipoprotein on days 3 and 28, an increase in plasma low-density lipoprotein on day 28 (p < 0.05), and marginal increases in total hepatic cholesterol on day 28 (p = 0.06). The observed changes are linked to APR. Although further research is needed to establish links between observations and the onset and progression of systemic disorders, the present study demonstrates the ability of NPs to induce systemic effects.
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) | 0.000 | 0.000 |
| 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) | 0.001 | 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".