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:

Carbon nanotubes-reinforced hollow fibre solid-phase microextraction coupled with high performance liquid chromatography for the determination of carbamate pesticides in apples. An effective and sensitive method to determinate five carbamate pesticides in apples was developed by using carbon nanotubes-reinforced hollow fibre solid-phase microextraction (CNTs-HF-SPME) combined with high performance liquid chromatography-photodiode array detection (HPLC-DAD). The CNTs were dispersed in water via adding surfactant, and then were held in the pores of HF supported by capillary forces and sonification. The SPME device, which was wetted with 1-octanol, was placed in a stirred apple samples to extract target analytes. After extraction, analytes were desorbed and analyzed using HPLC-DAD. Under the optimized extraction conditions, the enrichment factors were achieved in the range from 49 to 308 with good inter-fibre repeatability and batch-to-batch reproducibility, while good linearity ranges and recoveries were obtained. The limits of detection ranged from 0.09 to 6.00ng/g. Therefore, the results demonstrated that this novel method was an efficient pretreatment and enrichment procedure for the determination of trace carbamate pesticides in apples.
{"Chemical": ["carbon", "Carbon", "1-octanol", "carbamate"]}