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:

A New Face for Old Antibiotics: Tetracyclines in Treatment of Amyloidoses. The use of tetracyclines has declined because of the appearance of resistant bacterial strains. However, the indications of nonantimicrobial activities of these drugs have considerably raised interest and triggered clinical trials for a number of different pathologies. About 10 years ago we first reported that tetracyclines inhibited the aggregation of prion protein fragments and Alzheimer's β peptides, destabilizing their aggregates and promoting their degradation by proteases. On the basis of these observations, the antiamyloidogenic effects of tetracyclines on a variety of amyloidogenic proteins were studied and confirmed by independent research groups. In this review we comment on the data available on their antiamyloidogenic activity in preclinical and clinical studies. We also put forward that the beneficial effects of these drugs are a result of a peculiar pleiotropic action, comprising their interaction with oligomers and disruption of fibrils, as well as their antioxidant, anti-inflammatory, antiapoptotic, and matrix metalloproteinase inhibitory activities.
{"Chemical": ["Tetracyclines", "tetracyclines"]}