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:

Predictive modeling of insulin release profile from cross-linked chitosan microspheres. Insulin-loaded microspheres composed of chitosan 3% (w/v), and loading 120 IU insulin were produced by emulsion cross-linking method. Cross-linking time was 5 h and glutaraldehyde 3.5% (v/v) was used as cross-linker. Swelling ratio studies were evaluated to predict release of insulin from chitosan microspheres. Bacitracin and sodium taurocholate were incorporated in the formulations as proteolytic enzyme inhibitor and absorption enhancer, respectively. In vitro insulin release studies were performed in phosphate buffer pH 7.4 and also in HCl pH 2 with and without trypsin. Activity of bacitracin was also evaluated. In vitro release showed a controlled profile up to 12 h and the formulation containing 0.15% (w/v) of bacitracin revealed a maximum biological activity of about 49.1 ± 4.1%. Mathematical modeling using Higuchi and Korsmeyer-Peppas suggested a non-Fickian diffusion as the mechanism of insulin release. Insulin-loaded chitosan microspheres for oral delivery showed to be an innovative and reliable delivery system to overcome conventional insulin therapy.
{"Chemical": ["HCl", "glutaraldehyde", "sodium taurocholate", "bacitracin", "Bacitracin", "phosphate"]}