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:

Multi-cell type human liver microtissues for hepatotoxicity testing. Current 2-dimensional hepatic model systems often fail to predict chemically induced hepatotoxicity due to the loss of a hepatocyte-specific phenotype in culture. For more predictive in vitro models, hepatocytes have to be maintained in a 3-dimensional environment that allows for polarization and cell-cell contacts. Preferably, the model will reflect an in vivo-like multi-cell type environment necessary for liver-like responses. Here, we report the characterization of a multi-cell type microtissue model, generated from primary human hepatocytes and liver-derived non-parenchymal cells. Liver microtissues were stable and functional for 5 weeks in culture enabling, for example, long-term toxicity testing of acetaminophen and diclofenac. In addition, Kupffer cells were responsive to inflammatory stimuli such as LPS demonstrating the possibility to detect inflammation-mediated toxicity as exemplified by the drug trovafloxacin. Herewith, we present a novel 3D liver model for routine testing in 96-well format capable of reducing the risk of unwanted toxic effects in the clinic.
{"Chemical": ["acetaminophen", "trovafloxacin", "diclofenac"]}