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:

Evaluation of zebra mussels (Dreissena polymorpha) as biomonitors of mercury contamination in aquatic ecosystems. Zebra mussels have invaded many lakes in the United States and could be a useful tool for monitoring responses of aquatic biota to changes in mercury loading. The goal of the present study was to evaluate zebra mussels for use as a biomonitor of mercury contamination by comparing zebra mussel mercury concentrations between a lake with only indirect atmospheric mercury contamination (Otisco Lake, NY, USA) and a lake that was directly contaminated by mercury discharges (Onondaga Lake, NY, USA). Zebra mussels were sampled in both the spring and fall of 2004 and 2005. Total mercury (THg) concentrations in zebra mussels were approximately seven times greater in Onondaga Lake than in Otisco Lake, and water column mercury concentrations differed by an order of magnitude between the two lakes. Seasonal differences resulted in significantly higher zebra mussel THg concentrations during the fall for both lakes. There was also significant variation among different sampling sites in Onondaga Lake. Mussel methylmercury concentrations averaged 53% of THg concentrations but were highly variable. Strong relationships between water column THg and zebra mussel THg suggest that zebra mussels are a good indicator of aquatic mercury concentrations and could be used as an effective biomonitor of mercury contamination in aquatic ecosystems.
{"Chemical": ["mercury", "methylmercury"]}