Persistence of Isothiazolinones in Clothes After Machine Washing
Bibliographic record
Abstract
BACKGROUND: Sensitization to methylchloroisothiazolinone (MCI) and methylisothiazolinone (MI) is a worldwide problem. Washing machine detergents are suspected to cause cutaneous symptoms in highly sensitized patients. Little is known about the persistence of isothiazolinones in clothes that have been washed. OBJECTIVE: The aim of the study was to analyze the possible persistence of MI, MCI, benzisothiazolinone, and octylisothiazolinone in common fabrics after machine washing. METHODS: Different clothes (cotton, polyester, linen, and wool) were collected, and 4 types of wash were done (control, standard, standard + conditioner, and standard + double rinse). The samples were analyzed using ultrahigh-performance liquid chromatography. RESULTS: The results showed that the concentrations of isothiazolinones were very low, independent of the type of material or wash. The highest levels were found in the control wash (hand wash), reaching a maximum of 0.4 ppm in the linen. CONCLUSIONS: Our findings suggest that it is not necessary to recommend that patients sensitized to MI avoid isothiazolinones in machine detergents or fabric conditioners or to double rinse. However, after using the detergent for hand washing (the control in our study), there may remain sufficient concentrations of isothiazolinones in clothes to produce symptoms in highly sensitized patients.
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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 | 0.001 |
| 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) | 0.002 | 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".