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: ["Protein", "Chemical"].

Please return the output as a JSON object of the format: {"Chemical" : ["Dexamethasone", ...], "Protein" : ["BRCA-1", ...]}. 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:

Density of GM1 in nanoclusters is a critical factor in the formation of a spherical assembly of amyloid β-protein on synaptic plasma membranes.
The deposition of amyloid β-protein (Aβ) is a pathological hallmark of Alzheimer's disease (AD). We previously found that the ganglioside-enriched microdomains (ganglioside clusters) in presynaptic neuronal membranes play a key role in the initiation of the Aβ assembly process. However, not all ganglioside clusters accelerate Aβ assembly. In the present study, we directly observed a spherical Aβ in an atomic force microscopic study on the morphology of a reconstituted lipid bilayer composed of lipids that were extracted from a detergent-resistant membrane microdomain (DRM) fraction of synaptosomes prepared from aged mouse brain. The Aβ assembly was generated on a distinctive GM1 domain, which was characterized as the Aβ-sensitive ganglioside nanocluster (ASIGN). By using an artificial GM1 cluster-binding peptide, ASIGN was found to have a high density of GM1; therefore, there would be a critical density of GM1 in nanoclusters to induce Aβ binding and assembly. These results suggest that ganglioside-bound Aβ (GAβ), which acts as an endogenous seed for Aβ fibril formation in AD brains, is generated on ASIGN on synaptosomal membranes.
{"Chemical": ["ganglioside"], "Protein": ["amyloid \u03b2-protein", "A\u03b2", "GM1 domain"]}