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:

Magnetic Porous Sugar-Functionalized PEG Microgels for Efficient Isolation and Removal of Bacteria from Solution. Here we present a new microparticle system for the selective detection and magnetic removal of bacteria from contaminated solutions. The novelty of this system lies in the combination of a biocompatible scaffold reducing unspecific interactions with high capacity for bacteria binding. We apply highly porous poly(ethylene glycol) (PEG) microparticles and functionalize them introducing both sugar ligands for specific bacteria targeting and cationic moieties for electrostatic loading of superparamagnetic iron oxide nanoparticles. The resulting magnetic, porous, sugar-functionalized (MaPoS) PEG microgels are able to selectively bind and discriminate between different strains of bacteria Escherichia coli. Furthermore, they allow for a highly efficient removal of bacteria from solution as their increased surface area can bind three times more bacteria than non-porous particles. All in all, MaPoS particles represent a novel generation of magnetic beads introducing for the first time a porous, biocompatible and easy to functionalize scaffold and show great potential for various biotechnological applications.
{"Chemical": ["iron oxide", "sugar", "PEG", "poly(ethylene glycol)", "Sugar"]}