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:

Expanding the genetic code in Xenopus laevis oocytes. Heterologous expression of ligand-gated ion channels (LGICs) in Xenopus laevis oocytes combined with site-directed mutagenesis has been demonstrated to be a powerful approach to study structure-function relationships. In particular, introducing unnatural amino acids (UAAs) has enabled modifications that are not found in natural proteins. However, the current strategy relies on the technically demanding in vitro synthesis of aminoacylated suppressor tRNA. We report here a general method that circumvents this limitation by utilizing orthogonal aminoacyl-tRNA synthetase (aaRS)/suppressor tRNA(CUA) pairs to genetically encode UAAs in Xenopus oocytes. We show that UAAs inserted in the N-terminal domain of N-methyl-D-aspartate receptors (NMDARs) serve as photo-crosslinkers that lock the receptor in a discrete conformational state in response to UV photo treatment. Our method should be generally applicable to studies of other LGICs in Xenopus oocytes.
{"Chemical": ["N-methyl-D-aspartate", "N", "amino acids"]}