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:

Metabonomic Study of Genkwa Flos-induced Hepatotoxicity and Effect of Herb-Processing Procedure on Toxicity. A urinary metabonomic approach based on ultraperformance liquid chromatography coupled with mass spectrometry (UPLC-MS) was developed to study the metabolic disturbances caused by the administration of Genkwa Flos (GF) to rats. Potential biomarkers of GF-induced toxic effects were screened out and identified, and the underlying toxicological mechanism as well as the detoxification of vinegar-processing procedure on this herb was discussed. Urine samples were analyzed by the established UPLC-MS method. With the help of serum biochemistry and histopathology results, metabolic disturbances induced by the exposure to GF and the detoxification of processing procedure were confirmed. The differences in the metabolic profiles of healthy and treated rats were clearly discriminated with the principal component analysis of the chromatographic data. Eight significantly changed metabolites were identified and interpreted as biomarkers for the hepatotoxicity and detoxification of processing procedure. This study indicated that a UPLC-MS-based metabonomic analysis of urine samples could be considered as a promising tool to predict the hepatotoxicity induced by the GF and the detoxification of traditional vinegar-processing procedure on this herb. Copyright © 2012 John Wiley & Sons, Ltd.
{"Chemical": []}