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:

mGlu2/3 and mGlu5 receptors: potential targets for novel antidepressants. Major depressive disorder is among the most prevalent forms of mental illness. All currently available antidepressant medications have stemmed from study of the mechanisms of serendipitously discovered drugs, and only 30-50% of patients exhibit remission and frequently at least 3-4 weeks are required for manifestation of significant therapeutic effects. To overcome these drawbacks, discovering novel neuronal mechanisms of pathophysiology of depression as well as more effective treatments are necessary. This review focuses on the metabotropic glutamate (mGlu) receptors and their potential for drug targets for the treatment of depression. In particular, accumulating evidence has indicated the potential importance and usefulness of agents acting on mGlu2/3 and mGlu5 receptors. Preclinical and clinical evidence of mGlu2/3 receptor ligands and mGlu5 receptor antagonists are described. Moreover, their potential in clinic will be discussed in the context of neuronal mechanisms of ketamine, an agent recently demonstrated a robust effect for patients with treatment-resistant depression. This article is part of a Special Issue entitled 'Metabotropic Glutamate Receptors'.
{"Chemical": ["ketamine", "glutamate", "Glutamate"]}