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:

High-throughput screening of substrate chemistry for embryonic stem cell attachment, expansion, and maintaining pluripotency. Appropriate surface attachment is essential for growing embryonic stem (ES) cells in an undifferentiated state. It is challenging to identify the optimal surface chemistry of the substrata for ES cell attachment and maintenance. Using a rapid, high-throughput polymerization and screening platform with a comprehensive library of 66 monomer-grafted membrane surfaces, the optimal substrate, N-[3-(dimethylamino)propyl] methacrylamide (DMAPMA) has been identified to support strong attachment, high expansion capacity, and long-term self-renewal of ES cells (up to 7 passages). This monomer-based, chemically defined, scalable, sustainable, relatively inexpensive, covalently grafted, and controllable polymeric substrate provides a new opportunity to manipulate surface chemistry for pluripotent stem culture.
{"Chemical": ["N-[3-(dimethylamino)propyl] methacrylamide", "DMAPMA"]}