A novel affinity peptide library of igg constructed based on protein a affinity model and the application of the design method thereof
US-2015355192-A1 · Dec 10, 2015 · US
US10089435B1 · US · B1
| Field | Value |
|---|---|
| Publication number | US-10089435-B1 |
| Application number | US-201715667506-A |
| Country | US |
| Kind code | B1 |
| Filing date | Aug 2, 2017 |
| Priority date | Aug 2, 2017 |
| Publication date | Oct 2, 2018 |
| Grant date | Oct 2, 2018 |
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The field of this invention is classifying animal behaviors. In particular the fields of this invention include using animals in vivariums, such as rodents, particularly mice. When two mice socialize, a first mouse vocalizes a call and the second mouse vocalizes a response. Ultrasonic calls and responses are compared to video behaviors of the same mice, and then a table is constructed where each line comprises a particular call and response, a corresponding video behavior, and a correlation weight.
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We claim: 1. A device for automatically correlating animal vocalizations with animal behaviors comprising: a study animal type, wherein the study animal type is non-human; a vivarium comprising a set of study animals, of the study animal type, in a plurality of cages; a first animal of the study animal type in a first cage; a second animal of the study animal type in the first cage; at least one ultrasonic audio sensor proximal to the first cage, adapted to receive, from any animal in the first cage, audio vocalizations, and then communicate the audio vocalizations to a first processor; at least one video camera proximal to the first cage, adapted to detect and communicate one or more video behaviors of the first and second animals to the first processor; the first processor adapted to compare the audio vocalizations with the video behaviors; wherein an output of the first processor is a data table that comprises a plurality of tuples, where each tuple comprises: (i) a vocalization call by the first animal, and a vocalization response to the first animal's vocalization, by the second animal, (ii) a video behavior, (iii) a statistical correlation between (i) and (ii). 2. The device of claim 1 , wherein: the cages in the vivarium are free of electronic penetrations and are home cages of their respective animals. 3. The device of claim 1 , wherein: the at least one ultrasonic audio sensor proximal to the first cage is mechanically independent of the first cage such that the at least one ultrasonic audio sensor of the first cage may be replaced without mechanically moving the first cage or the at least one ultrasonic audio sensor, respectively. 4. The device of claim 1 , wherein: the device is free of manually observed behavior of the study animals, and free of manually communicated to a processor behavior of the study animals, and free of manual classifying of sets of behaviors. 5. The device of claim 1 , wherein: the detection and communication of animal behaviors is continuous. 6. A method of classifying animal behaviors using a system comprising: a study animal type, wherein the study animal type is non-human; a vivarium comprising a set of study animals, of the study animal type, in a plurality of cages; a first animal of the study animal type in a first cage; a second animal of the study animal type in the first cage; at least one ultrasonic audio sensor proximal to the first cage, adapted to receive, from any animal in the first cage, audio vocalizations, and then communicate the audio vocalizations to a first processor; at least one video camera proximal to the first cage, adapted to detect and communicate one or more video behaviors of the first and second animals to the first processor; the first processor adapted to compare the audio vocalizations with the video behaviors; wherein an output of the first processor is a data table that comprises a plurality of tuples, where each tuple comprises: (i) a vocalization call by the first animal, and a vocalization response to the first animal's vocalization, by the second animal, (ii) a video behavior, (iii) a statistical correlation weight between (i) and (ii); wherein steps of the method comprise: (a) placing into a the vivarium the set of study animals into the plurality of cages; (b) communicating the audio vocalizations from the at least one ultrasonic audio sensor to the first processor; (c) communicating the one or more video behaviors of the first and second animals to the first processor; (d) outputting by the first processor the data table that comprises a plurality of tuples, where each tuple comprises: (i) a vocalization call by the first animal, and a vocalization response to the first animal's vocalization, by the second animal, (ii) a video behavior, (iii) a statistical correlation weight between (i) and (ii). 7. A system of classifying animal behaviors comprising: a study animal type, wherein the study animal type is non-human; a vivarium comprising a set of study animals, of the study animal type, in a plurality of cages; a first animal of the study animal type in a first cage; a second animal of the study animal type in the first cage; at least one ultrasonic audio sensor proximal to the first cage, adapted to receive, from any animal in the first cage, audio vocalizations, and then communicate the audio vocalizations to a first processor; at least one video camera proximal to the first cage, adapted to detect and communicate one or more video behaviors of the first and second animals to the first processor; the first processor adapted to compare the audio vocalizations with the video behaviors; wherein an output of the first processor is a data table that comprises a plurality of tuples, where each tuple comprises: (i) a vocalization call by the first animal, and a vocalization response to the first animal's vocalization, by the second animal, (ii) a video behavior, (iii) a statistical correlation weight between (i) and (ii).
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