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:

Novel quinolone substituted thiazolidin-4-ones as anti-inflammatory, anticancer agents: Design, synthesis and biological screening. Nuclear factor-kappaB (NF-κB) has been reported to regulate various genes involved in cancer and inflammation. Accordingly, drugs suppressing or inhibiting NF-κB may possess both anti-inflammatory and anticancer properties. A library of quinolone substituted thiazolidin-4-ones was docked into the active site of NF-κB and the top-ranked 31 compounds were synthesized and evaluated for anti-inflammatory and anticancer activity. The best-ranked compound 6b showed highest anti-inflammatory activity in carrageenan-induced paw edema model. In vitro anticancer studies revealed 1a and 16a as most active compounds against BT-549, HeLa, COLO-205 and ACHN human cancer cell lines. Compounds 1a and 16a exhibited NF-κB dependent anticancer properties and apoptosis mediated cell death. In vivo Ehrlich ascites carcinoma study further confirmed the antitumor activity of 1a and 16a.
{"Chemical": ["quinolone", "thiazolidin-4-ones"]}