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:

Performances of CN-columns for the analysis of γ-oryzanol and its p-coumarate and caffeate derivatives by normal phase HPLC and a validated method of quantitation. γ-Oryzanol is an important phytochemical used in pharmaceutical, alimentary and cosmetic preparations. The present article, for the first time, discloses the performances of NP-HPLC in separating γ-oryzanol components and develops a validated method for its routine quantification. The analysis is performed on a cyanopropyl bonded column using the hexane/MTBE gradient elution and UV detection at 325 nm. The method allows: the separation of steryl ferulate, p-coumarate and caffeate esters, the separation of cis- from trans-ferulate isomers, the splitting of steroid moieties into saturated and unsaturated at the side chain. The optimised method provides excellent linear response (R(2)=0.99997), high precision (RSD<1.0%) and satisfactory accuracy (R(∗)=70-86%). In conclusion, the established method presents the details of the procedure and the experimental conditions in order to achieve the required precision and instrumental accuracy. The method is fast and sensitive and it could be a suitable tool for quality assurance and determination of origin.
{"Chemical": ["\u03b3-oryzanol", "steryl ferulate", "\u03b3-Oryzanol", "cyanopropyl", "p-coumarate", "caffeate", "hexane", "steroid", "MTBE", "trans-ferulate", "caffeate esters"]}