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:

Structural Basis of Signaling Blockade by Anti-IL-13 Antibody Lebrikizumab. The cytokine interleukin 13 (IL-13) is a major effector molecule for T-helper type 2 inflammation and is pathogenic in allergic diseases such as asthma. The effects of IL-13 are mediated via a pathway that is initiated by binding to a heterodimeric receptor consisting of IL-13Rα1 and IL-4Rα. Antibodies raised against IL-13 can block its inflammatory effects by interfering with binding to either of the two receptor polypeptides. Lebrikizumab is a monoclonal anti-IL-13 antibody that has shown clinical benefit in a phase II study for the treatment of moderate-to-severe uncontrolled asthma. Here we report the molecular structure of IL-13 in complex with the Fab from lebrikizumab by X-ray crystallography at 1.9Å resolution. We show that lebrikizumab inhibits IL-13 signaling by binding to IL-13 with very high affinity and blocking IL-13 binding to IL-4Rα. In addition, we use site-directed mutations to identify the most important antibody contributors to binding. Our studies define key features of lebrikizumab binding and its mechanism of action that may contribute to its clinical effects.
{"Chemical": []}