Early and Delayed Effects of Naturally Occurring Asbestos on Serum Biomarkers of Inflammation and Metabolism
Bibliographic record
Abstract
Studies recently showed that intratracheal (IT) instillation of Libby amphibole (LA) increases circulating acute-phase proteins (APP; α-2 macroglobulin, A2M; and α-1 acid glycoprotein, AGP) and inflammatory biomarkers (osteopontin and lipocalin) in rats. In this study, objectives were to (1) compare changes in biomarkers of rats after instillation of different naturally occurring asbestos (NOA) minerals including LA, Sumas Mountain chrysotile (SM), El Dorado Hills tremolite (ED), and Ontario ferroactinolite cleavage fragments (ON), and (2) examine biomarkers after subchronic LA or amosite inhalation exposure. Rat-respirable fractions (aerodynamic diameter approximately 2.5 μm) prepared by water elutriation were delivered via a single IT instillation at doses of 0, 0.5, and 1.5 mg/rat in male F344 rats. Nose-only inhalation exposures were performed at 0, 1, 3.3, and 10 mg/m(3) for LA and at 3.3 mg /m(3) for amosite, 6h/d, 5 d/wk for 13 wk. Inflammation, metabolic syndrome, and cancer biomarkers were analyzed in the serum for up to 18 mo. IT instillation of some asbestos materials significantly increased serum AGP and A2M but to a varying degree (SM = LA > ON = ED). Numerical increases in interleukin (IL)-6 and osteopontin occurred in rats instilled with SM. SM and ED also elevated leptin and insulin at 15 mo, suggesting potential metabolic effects. LA inhalation tended to raise A2M at d 1 but not cytokines. Serum mesothelin appeared to elevate after 18 mo of LA inhalation. These results suggest that the lung injury induced by high levels of asbestos materials may be associated with systemic inflammatory changes and predisposition to insulin resistance.
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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 | 0.000 |
| 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 | 0.001 |
| 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".