Concordance between In Vitro and In Vivo Relative Toxic Potencies of Diesel Exhaust Particles from Different Biodiesel Blends
Bibliographic record
Abstract
Diesel exhaust particles (DEPs) contribute to air pollution exposure-related adverse health impacts. Here, we examined in vitro, and in vivo toxicities of DEPs from a Caterpillar C11 heavy-duty diesel engine emissions using ultra-low-sulfur diesel (ULSD) and biodiesel blends (20% v/v) of canola (B20C), soy (B20S), or tallow–waste fry oil (B20T) in ULSD. The in vitro effects of DEPs (DEPULSD, DEPB20C, DEPB20S, and DEPB20T) in exposed mouse monocyte/macrophage cells (J774A.1) were examined by analyzing the cellular cytotoxicity endpoints (CTB, LDH, and ATP) and secreted proteins. The in vivo effects were assessed in BALB/c mice (n = 6/group) exposed to DEPs (250 µg), carbon black (CB), or saline via intratracheal instillation 24 h post-exposure. Bronchoalveolar lavage fluid (BALF) cell counts, cytokines, lung/heart mRNA, and plasma markers were examined. In vitro cytotoxic potencies (e.g., ATP) and secreted TNF-α were positively correlated (p < 0.05) with in vivo inflammatory potency (BALF cytokines, lung/heart mRNA, and plasma markers). Overall, DEPULSD and DEPB20C appeared to be more potent compared to DEPB20S and DEPB20T. These findings suggested that biodiesel blend-derived DEP potencies can be influenced by biodiesel sources, and inflammatory process- was one of the potential underlying toxicity mechanisms. These observations were consistent across in vitro and in vivo exposures, and this work adds value to the health risk analysis of cleaner fuel alternatives.
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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 | 0.000 |
| 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) | 0.001 | 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".