Systematic review of the human health hazards of propylene dichloride
Bibliographic record
Abstract
Propylene dichloride (PDC) is a chlorinated substance used primarily as an intermediate in basic organic chemical manufacturing. The United States Environmental Protection Agency (EPA) is currently evaluating PDC as a high-priority substance under the Toxic Substances Control Act (TSCA). We conducted a systematic review of the non-cancer and cancer hazards of PDC using the EPA TSCA and Integrated Risk Information System (IRIS) frameworks. We identified 12 epidemiological, 16 toxicokinetic, 34 experimental animal, and 49 mechanistic studies. Point-of-contact respiratory effects are the most sensitive non-cancer effects after inhalation exposure, and PDC is neither a reproductive nor a developmental toxicant. PDC is not mutagenic in vivo, and while in vitro evidence is mixed, DNA strand breaks consistently occur. Nasal tumors in rats and lung tumors in mice occurred after lifetime high-level inhalation exposure. Cholangiocarcinoma (CCA) was observed in Japanese print workers exposed to high concentrations of PDC. However, co-exposures, as well as liver parasites, hepatitis, and other risk factors, may also have contributed. The cancer mode of action (MOA) analysis revealed that PDC may act through multiple biological pathways occurring sequentially and/or simultaneously, although chronic tissue damage and inflammation likely dominate. Critically, health benchmarks protective of non-cancer effects are expected to protect against cancer in humans.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".