You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["Chemical"].

Please return the output as a JSON object of the format: {"Chemical": ["Arsenic", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

Toxicokinetics of methyleugenol in F344 rats and B6C3F₁ mice. 1. Methyleugenol (MEG) has been used as a flavouring agent in food, as a fragrance in cosmetic products, and as an insect attractant. MEG was carcinogenic in both rats and mice following gavage administration. In this study we investigated plasma toxicokinetics of MEG in F344 rats and B6C3F₁ mice of both sexes following single gavage (37, 75, or 150 mg/kg) and intravenous (IV) (37 mg/kg) administration. 2. Following IV administration, MEG was rapidly distributed and cleared from the systemic circulation in both species and sexes. Absorption of MEG was rapid following gavage administration with secondary peaks in the plasma MEG concentration-versus-time profiles. C(max) and AUC(T) increased and the clearance decreased greater than proportional to the dose in rats and mice of both sexes. In general, rats had higher internal exposure to MEG than mice. 3. The results for AUC(T) and clearance suggest that perhaps the metabolism of MEG is saturated at higher doses tested in this study. Absolute bioavailability following gavage administration of 37 mg/kg was low in both rats (~4%) and mice (7-9%) of both sexes indicating extensive first-pass metabolism. There was no sex difference in plasma toxicokinetics of MEG following gavage administration both in rats and mice.
{"Chemical": ["Methyleugenol", "MEG", "methyleugenol"]}