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:

Achieving automated scorpion venom mass fingerprinting (VMF) in the nanogram range. During the past decade mass spectrometry (MS) has become one of the major suitable techniques for peptide and protein analysis from animal venoms, not only to identify new toxins within these complex mixtures, but also for toxin structural studies. The goal of the experiments presented here was to test the ultimate limit for producing scorpion venom mass fingerprinting (VMF; i.e. a comprehensive list of all masses in presence). Thanks to recent developments in nano ultra high performance liquid chromatography (UHPLC) and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/MS), we sought the experimental conditions for setting up an automated data acquisition workflow. As the main result, we demonstrate the possibility to easily achieve VMF having in hand only tens of nanogram of venom. ELISA on-line was also beneficial to monitor in the picogram range for toxin families using specific antisera raised against major toxins.
{"Chemical": []}