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:

Correlation of high urinary Smad1 level with glomerular hyperfiltration in type 2 diabetes mellitus. The aim of this study was to assess the relationship between urinary Smad1 and glomerular hyperfiltration (GHF) in type 2 diabetes mellitus (T2DM), and to explore the factors related to the urinary Smad1 in T2DM. The reference value of the estimated glomerular filtration rate (eGFR) was determined in 248 healthy individuals. 30 patients with GHF, 58 patients with norm-GFR T2DM, and 24 healthy patients who served as controls were recruited. Urinary Smad1, fasting plasma glucose (FPG), fasting serum C-Peptide (C-P), hemoglobin A1C (HbA1c), cystatin C, and other chemistry laboratory parameters of T2DM participants and controls were measured. Patients with GHF had higher levels of urinary Smad1 than the control group, and those with norm-GFR. For T2DM patients with body mass index, age, and gender adjustments, urinary Smad1 was positively correlated with FPG, HbA1C, and eGFR, but negatively correlated with fasting serum C-P. Multivariate linear regression analysis demonstrated that eGFR, HbA1C, and fasting serum C-P were independently associated with urinary Smad1. High levels of urinary Smad1 were found in GHF patients with T2DM, which may be another potential mechanism of GHF in relation to diabetic nephropathy.
{"Chemical": ["glucose"]}