Absence of a Causal Link between Elemental Carbon Exposure and Short-Term Respiratory Toxicity in Human-Derived Organoids and Cellular Models
Bibliographic record
Abstract
Abstract Black carbon or elemental carbon (EC) in the atmosphere plays an ambiguous role in acute respiratory toxic effects. Here, we evaluate the contribution of EC to the short-term toxicity (including cytotoxicity and oxidative stress potency) of fine particulate matter (PM2.5) on the human respiratory tract using in vitro airway organoids and cell lines. The toxic potency of EC per unit mass, including char and soot, is more than 2 orders of magnitude lower than that of polycyclic aromatic hydrocarbons (PAHs), which are coemitted from incomplete combustion. EC contributes approximately 1 order of magnitude less to PM2.5 toxicity than PAHs, despite its positive associations with PM2.5-induced toxic potency (p < 0.0001). Furthermore, PAHs contribute 71.9 ± 12.2% and 61.9 ± 32.8% of the overall toxic potency of PM2.5 emitted from typical incomplete burning of solid and liquid fuels, respectively, while the PM2.5 toxicity significantly correlates with PAHs content (r = 0.94, p = 0.002). Hence, EC is not a cause of inducing acute toxicity, likely attributed to coemitted PAHs. These findings provide causal evidence for understanding the respiratory health risks associated with exposure to PM2.5 and further benefit to establishing efficient air pollution control policies.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".