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:

Unusual glycosaminoglycans from a deep sea hydrothermal bacterium improve fibrillar collagen structuring and fibroblast activities in engineered connective tissues. Biopolymers produced by marine organisms can offer useful tools for regenerative medicine. Particularly, HE800 exopolysaccharide (HE800 EPS) secreted by a deep-sea hydrothermal bacterium displays an interesting glycosaminoglycan-like feature resembling hyaluronan. Previous studies demonstrated its effectiveness to enhance in vivo bone regeneration and to support osteoblastic cell metabolism in culture. Thus, in order to assess the usefulness of this high-molecular weight polymer in tissue engineering and tissue repair, in vitro reconstructed connective tissues containing HE800 EPS were performed. We showed that this polysaccharide promotes both collagen structuring and extracellular matrix settle by dermal fibroblasts. Furthermore, from the native HE800 EPS, a low-molecular weight sulfated derivative (HE800 DROS) displaying chemical analogy with heparan-sulfate, was designed. Thus, it was demonstrated that HE800 DROS mimics some properties of heparan-sulfate, such as promotion of fibroblast proliferation and inhibition of matrix metalloproteinase (MMP) secretion. Therefore, we suggest that the HE800EPS family can be considered as an innovative biotechnological source of glycosaminoglycan-like compounds useful to design biomaterials and drugs for tissue engineering and repair.
{"Chemical": ["sulfate"]}