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:

Preparation of apigenin nanocrystals using supercritical antisolvent process for dissolution and bioavailability enhancement. The aim of the study was to investigate the potential of nanocrystals to enhance the oral bioavailability of apigenin (AP), a bioactive flavonoid with various pharmacological activities but poor aqueous solubility. In the present investigation, the AP nanocrystals were prepared by the supercritical antisolvent process. In vitro characterization was performed by scanning electron microscopy, FT-IR, differential scanning calorimetry, X-ray powder diffractometry. In vitro dissolution of prepared nanocrystals was studied and compared with untreated coarse powder. In addition, the pharmacokinetic study of AP nanocrystals, in comparison to coarse powder, was also performed in rats after a single oral dose. The prepared AP nanocrystals, without change in crystalline structure, appeared in spherical shape with particle size of about 400-800 nm. The reduction of particle size resulted in a more rapid dissolution of AP from nanocrystals than from coarse powder. In comparison to coarse powder, AP nanocrystals exhibited a significantly decreased t(max), a 3.6-fold higher peak plasma concentration (C(max)) and 3.4-fold higher area under the curve (AUC).
{"Chemical": ["apigenin", "flavonoid"]}