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:

Dietary composition of carbohydrates contributes to the development of experimental type 2 diabetes. Evidence has emerged supporting a link between high glycaemic index (GI) diets and type 2 diabetes (T2D). The aim of this study was to determine if dietary GI influences the development of hyperglycaemia in C57BL/6 mice to more closely reflect T2D. Male C57BL/6 mice (n=30) were randomly divided into 3 dietary groups consisting of either standard rodent chow (4.8 % fat, 20 % protein), or a high fat (HF) diet (21-23 % fat, 19 % protein) with low GI (15.4 % starch; HF-LG) or high GI (50.5 % dextrose; HF-HG) ad libitum for 10 weeks. Body weight, blood glucose, glucose tolerance, and circulating cholesterol and triglyceride levels were measured for the duration of the study. We found that increasing the GI of a moderately HF diet induces severe hyperglycaemia and insulin resistance in C57BL/6 mice, reflective of criteria for diagnosis of T2D, whilst littermates consuming an equivalent low GI diet maintain glucose homeostasis. This study demonstrates the significant contribution of both dietary carbohydrate and fat composition in the aetiopathogenesis of T2D.
{"Chemical": ["carbohydrates", "glucose", "carbohydrate", "dextrose", "triglyceride", "cholesterol"]}