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:

The in vivo antioxidant and antifibrotic properties of green tea (Camellia sinensis, Theaceae). The in vivo antioxidant and antifibrotic properties of green tea (Camellia sinensis, Theaceae) were investigated with a study of carbon tetrachloride (CCl(4))-induced oxidative stress and hepatic fibrosis in male ICR mice. Oral administration of green tea extract at doses of 125, 625 and 1250 mg/kg for 8 weeks significantly reduced (p<0.05) the levels of thiobarbituric acid-reactive substances (TBARS) and protein carbonyls in the liver by at least 28% compared with that was induced by CCl(4) (1 mL/kg) in mice. Moreover, green tea extract administration significantly increased (p<0.05) the activities of catalase, glutathione peroxidase (GSH-Px) and glutathione reductase (GSH-Rd) in the liver. Our study found that oral administration of green tea extract prevented CCl(4)-induced hepatic fibrosis, as evidenced by a decreased hydroxyproline level in the liver and a reduced incidence of hepatic fibrosis by histological observations. These results indicate that green tea exhibits potent protective effects against CCl(4)-induced oxidative stress and hepatic fibrosis in mice by inhibiting oxidative damage and increasing antioxidant enzyme activities.
{"Chemical": ["glutathione", "hydroxyproline", "GSH", "thiobarbituric acid", "carbonyls", "carbon tetrachloride", "CCl(4)"]}