A Deep Dive into the Complex Chemical Mixture and Toxicity of Tire Wear Particle Leachate in Fathead Minnow
Bibliographic record
Abstract
Abstract The ecological impact of tire wear particles in aquatic ecosystems is a growing environmental concern. We combined toxicity testing, using fathead minnow (Pimephales promelas) embryos, with nontarget high-resolution liquid chromatography Orbitrap mass spectrometry to characterize the toxicity and chemical mixture of organic chemicals associated with tire particle leachates. We assessed: 1) exposure to tire particle leachates after leaching for 1-, 3-, and 10-d; and 2) the effect of the presence and absence of small tire particulates in the leachates. We observed a decrease in embryonic heart rates, hatching success, and lengths, as well as an increase in the number of embryos with severe deformities and diminished eye and body pigmentation, after exposure to the leachates. Overall, there was a pattern whereby we observed more toxicity in the 10-d leachates, and greater toxicity in unfiltered leachates. Redundancy analysis showed that several benzothiazoles and aryl-amines were correlated with the toxic effects observed in the embryos. These included benzothiazole, 2-aminobenzothiazole, 2-mercaptobenzothiazole, N,N′-diphenylguanidine, and N,N′-diphenylurea. However, many other chemicals characterized as unknowns are likely to also play a key role in the adverse effects observed. Our study provides insight into the types of chemicals likely to be important toxicological drivers in tire leachates, and improves our understanding of the ecotoxicological impacts of tire wear particles. Environ Toxicol Chem 2022;41:1144–1153. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. Abstract Redundancy analysis (RDA) shows positive correlations between chemicals benzothiazoles and aryl-amines in tire leachates, and increased hatch severity and lack of pigmentation in fathead minnow embryos. OHBT = hydroxybenzothiazole; PBI = 3-phenyl-1,3-benzothiazol-2-imine; NHBT = 2-aminobenzothiazole; MeSBT = 2-(methylthio)benzothiazole; MBT = 2-mercaptobenzothiazole; DPG = N,N′-diphenylguanidine; CPU = cyclohexyl-3-phenylurea; DHU = N,N′-dicyclohexylurea; DPU = N,N′-diphenylurea; DHPA = 4,5-diphenyl-1H-pyrazole-3-amine; DHA = dicyclohexylamine; HM = hexa(methoxymethyl)melamine; ABZ = 3-aminobenzamide; BT = benzothiazole; ACT = acetoacetanilide; TMQ = 1,2-Dihydro-2,2,4-trimethylquinoline; ACR = acridene.
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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) | 0.000 | 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".