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:

Transglutaminase cross-linking effect on sensory characteristics and antioxidant activities of Maillard reaction products from soybean protein hydrolysates. To improve the yield of Maillard peptides, a microbial transglutaminase (MTGase) was used to increase the content of 1000-5000Da peptides in soybean protein hydrolysates by using a cross-linking reaction. The sensory characteristics and antioxidant activities of corresponding Maillard Reaction Products (MSPC) was then evaluated. After cross-linking treatment the content of 1000-5000Da peptides in protein hydrolysates and the yield of Maillard peptides increased by 21.19% and 8.71%, respectively, which contributed to the improved mouthfulness of MSPC. The bitter amino acids were significantly decreased and the umami acids were markedly increased in MSPC. Volatile compounds identified by GC-MS analysis showed that the content of the important meaty flavour compounds (such as 2-methyl-3-furanthiol, bis(2-methyl-3-furyl)disulfide) of MSPC were dramatically higher than that of MRPs from uncross-linking peptides. Combined with sensory evaluation, it was confirmed that MTGase cross-linking improved the flavour Characteristics and did not affect the antioxidant activity of MSPC.
{"Chemical": ["bis(2-methyl-3-furyl)disulfide", "2-methyl-3-furanthiol", "amino acids"]}