A 45-year-old male patient was admitted to the Regional Poison Center because of poisoning with dimethyloaniline contained in a toxic resin-curing dimethyl aniline-based formulation ingested inadvertently. Intoxication happened at workplace. The patient was then transferred to the Toxicology Clinic, where he stayed for 3 weeks. During the hospitalization, the primary method of treatment involved administration of methylene blue, which is the antidote of choice in such cases. During the intensive care and treatment of the patient massive intravascular hemolysis was seen. In that case treatment with blood products was required. He also showed signs of liver dysfunction due to cholestatic liver damage and jaundice. The reported case shows that severe organ damage may result from poisoning with even a small amount of the toxicant. Med Pr 2017;68(6):795-801.
Do regionalnego ośrodka zatruć (ROZ) przyjęto 45-letniego pacjenta z powodu omyłkowego zatrucia pochodną dimetyloaniliny w miejscu pracy. Substancja toksyczna trafiła do organizmu drogą doustną. Podczas hospitalizacji podstawowym sposobem leczenia było podawanie błękitu metylenowego jako klasycznej odtrutki stosowanej w takim przypadku. W trakcie intensywnej opieki i leczenia u pacjenta zaobserwowano masywną hemolizę wewnątrznaczyniową, wymagającą leczenia preparatami krwiopochodnymi, oraz cechy uszkodzenia wątroby w postaci cholestatycznego uszkodzenia wątroby i żółtaczki. W Klinice Toksykologii pacjent przebywał 3 tygodnie. Opisany przypadek wskazuje na możliwość wystąpienia ciężkich powikłań narządowych w przebiegu zatrucia nawet niewielką ilością substancji chemicznej. Med. Pr. 2017;68(6):795–801.

Predictive toxicity models rely on large amounts of accurate in vivo data. Here, we analyze the quality of in vivo data from the U.S. EPA Toxicity Reference Database (ToxRefDB), using chemical-induced anemia as an example. Considerations include variation in experimental conditions, changes in terminology over time, distinguishing negative from missing results, observer and diagnostic bias, and data transcription errors. Within ToxRefDB, we use hematological data on 658 chemicals tested in one or more of 1738 studies (subchronic rat or chronic rat, mouse, or dog). Anemia was reported most frequently in the rat subchronic studies, followed by chronic studies in dog, rat, and then mouse. Concordance between studies for a positive finding of anemia (same chemical, different laboratories) ranged from 90% (rat subchronic predicting rat chronic) to 40% (mouse chronic predicting rat chronic). Concordance increased with manual curation by 20% on average. We identified 49 chemicals that showed an anemia phenotype in at least two species. These included 14 aniline moiety-containing compounds that were further analyzed for their potential to be metabolically transformed into substituted anilines, which are known anemia-causing chemicals. This analysis should help inform future use of in vivo databases for model development.