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:

Enrichment of two isoflavone aglycones in black soymilk by using spent coffee grounds as an immobiliser for β-glucosidase. Spent coffee grounds, discarded as environmental pollutants, were adopted as enzyme immobilisation solid carriers instead of commercialised solid supports to establish an economical catalytic system. β-Glucosidase was covalently immobilised onto spent coffee grounds for the conversion of isoflavone glycosides into their aglycones in black soymilk. Optimum conditions were determined to be 40°C and pH 6 using 4-nitrophenyl β-d-glucuronide as an indicator. Operational reusability was confirmed for more than 30 batch reactions and the storage stability was capable of sustaining its highest catalytic activity for 20days. The kinetic parameters including rate constant (K), time (τ50) in which 50% of isoflavone deglycosylation was reached, and time (τcomplete) required to achieve complete isoflavone deglycosylation, were0.16±0.02min(-1), 4.54±0.32min, 60min for daidzin and 0.16±0.02min(-1), 2.28±0.11min, 60min for genistin, respectively. The total aglycone content in black soymilk was enriched by 67.14±0.60% in the enzymatic treatment of 60min duration.
{"Chemical": ["daidzin", "isoflavone", "isoflavone glycosides", "genistin", "isoflavone aglycones", "4-nitrophenyl \u03b2-d-glucuronide"]}