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:

Positive Regulation of Insulin Signaling by Neuraminidase 1. Neuraminidases (sialidases) catalyze the removal of sialic acid residues from sialylated glycoconjugates. We now report that mammalian neuraminidase 1 (Neu1), in addition to its catabolic function in lysosomes, is transported to the cell surface where it is involved in regulation of insulin signaling. Insulin binding to its receptor rapidly induces interaction of the receptor with Neu1, which hydrolyzes sialic acid residues in the glycan chains of the receptor and, consequently, induces its activation. Cells from sialidosis patients with a genetic deficiency of Neu1 show impairment of insulin-induced phosphorylation of downstream protein kinase AKT, while treatment of these cells with purified Neu1 restores signaling. Genetically-modified mice with ∼10% of the normal Neu1 activity exposed to a high-fat diet develop hyperglycemia and insulin resistance twice as fast as their wild type counterparts. Together, these studies identify Neu1 as a novel component of the signaling pathways of energy metabolism and glucose uptake.
{"Chemical": ["glucose", "sialic acid"]}