Abstract: The compositions and methods are described for generating an immune response to a Plasmodium antigen. The compositions and methods described herein relate to a modified vaccinia Ankara (MVA) vector encoding one or more viral antigens for generating a protective immune response to malaria by expressing the Plasmodium antigen in the subject to which the MVA vector is administered. The compositions and methods of the present invention are useful both prophylactically and therapeutically and may be used to prevent and/or treat malaria.

Abstract: The compositions and methods are described for generating an immune response to a Plasmodium antigen. The compositions and methods described herein relate to a modified vaccinia Ankara (MVA) vector encoding one or more viral antigens for generating a protective immune response to malaria by expressing the Plasmodium antigen in the subject to which the MVA vector is administered. The compositions and methods of the present invention are useful both prophylactically and therapeutically and may be used to prevent and/or treat malaria.

Abstract: Systems, devices, and methods are disclosed for wireless communication of analyte data. In this regard, in embodiments, a mobile includes a transceiver configured to transmit and receive wireless signals. The mobile device includes circuitry operatively coupled to the transceiver. The mobile device also includes a non-transitory computer-readable medium operatively coupled to the circuitry and storing instructions that, when executed, cause the mobile device to perform a number of operations. One such operation is to obtain a derivative of a first signal received via a first link. Another such operation is to obtain a derivative of a second signal received via a second link; and. Yet another such operation is to generate a selection for connection to an analyte sensor system, based on a comparison of the derivative of the first signal and the derivative of the second signal.

Abstract: The compositions and methods are described for generating an immune response to a flavivirus such as Zika virus. The compositions and methods described herein relate to a modified vaccinia Ankara (MVA) vector encoding one or more viral antigens for generating a protective immune response to a member of genus Flavivirus (such as a member of species Zika virus), in the subject to which the vector is administered. The compositions and methods of the present invention are useful both prophylactically and therapeutically and may be used to prevent and/or treat an infection caused by Flavivirus.

Abstract: Systems, devices, and methods are disclosed for wireless communication of analyte data. In this regard, in embodiments, a mobile includes a transceiver configured to transmit and receive wireless signals. The mobile device includes circuitry operatively coupled to the transceiver. The mobile device also includes a non-transitory computer-readable medium operatively coupled to the circuitry and storing instructions that, when executed, cause the mobile device to perform a number of operations. One such operation is to obtain a derivative of a first signal received via a first link. Another such operation is to obtain a derivative of a second signal received via a second link; and. Yet another such operation is to generate a selection for connection to an analyte sensor system, based on a comparison of the derivative of the first signal and the derivative of the second signal.

Abstract: The compositions and methods are described for generating an immune response to an antigen. The compositions and methods described herein relate to a modified vaccinia Ankara (MVA) vector encoding one or more viral antigens as a fusion product with a viral glycoprotein and matrix protein for generating a protective immune response to a subject to which the vector is administered. The compositions and methods of the present invention are useful both prophylactically and therapeutically and may be used to prevent and/or treat diseases.

Abstract: The compositions and methods are described for generating an immune response to a Plasmodium antigen. The compositions and methods described herein relate to a modified vaccinia Ankara (MVA) vector encoding one or more viral antigens for generating a protective immune response to malaria by expressing the Plasmodium antigen in the subject to which the MVA vector is administered. The compositions and methods of the present invention are useful both prophylactically and therapeutically and may be used to prevent and/or treat malaria.

Abstract: The compositions and methods are described for generating an immune response to an antigen. The compositions and methods described herein relate to a modified vaccinia Ankara (MVA) vector encoding one or more viral antigens as a fusion product with a viral glycoprotein and matrix protein for generating a protective immune response to a subject to which the vector is administered. The compositions and methods of the present invention are useful both prophylactically and therapeutically and may be used to prevent and/or treat diseases.

Abstract: The compositions and methods are described for generating an immune response to a Plasmodium antigen. The compositions and methods described herein relate to a modified vaccinia Ankara (MVA) vector encoding one or more viral antigens for generating a protective immune response to malaria by expressing the Plasmodium antigen in the subject to which the MVA vector is administered. The compositions and methods of the present invention are useful both prophylactically and therapeutically and may be used to prevent and/or treat malaria.

Abstract: The compositions and methods are described for generating an immune response to a tumor associated antigen such as MUC1. The compositions and methods described herein relate to a modified vaccinia Ankara (MVA) vector encoding one or more viral antigens for generating a protective immune response to a neoplasm expressing the tumor associated antigen in the subject to which the vector is administered. The compositions and methods of the present invention are useful both prophylactically and therapeutically and may be used to prevent and/or treat neoplasms and associated diseases.

Abstract: Systems, devices, and methods are disclosed for wireless communication of analyte data. In this regard, in embodiments, a mobile includes a transceiver configured to transmit and receive wireless signals. The mobile device includes circuitry operatively coupled to the transceiver. The mobile device also includes a non-transitory computer-readable medium operatively coupled to the circuitry and storing instructions that, when executed, cause the mobile device to perform a number of operations. One such operation is to obtain a derivative of a first signal received via a first link. Another such operation is to obtain a derivative of a second signal received via a second link; and. Yet another such operation is to generate a selection for connection to an analyte sensor system, based on a comparison of the derivative of the first signal and the derivative of the second signal.

Abstract: Techniques and protocols for establishing secure communications between a display device, a sensor system, and a server system are disclosed. In certain embodiments, the techniques and protocols include secure diabetes device identification techniques and protocols, user-centric mutual authentication techniques and protocols, and device-centric mutual authentication techniques and protocols.

Abstract: Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.

Abstract: Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.

Abstract: Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.

Abstract: Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.

Abstract: Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.

Abstract: Systems, devices, and methods are disclosed for wireless communication of analyte data. In this regard, in embodiments, a mobile includes a transceiver configured to transmit and receive wireless signals. The mobile device includes circuitry operatively coupled to the transceiver. The mobile device also includes a non-transitory computer-readable medium operatively coupled to the circuitry and storing instructions that, when executed, cause the mobile device to perform a number of operations. One such operation is to obtain a derivative of a first signal received via a first link. Another such operation is to obtain a derivative of a second signal received via a second link; and. Yet another such operation is to generate a selection for connection to an analyte sensor system, based on a comparison of the derivative of the first signal and the derivative of the second signal.

Abstract: Systems, devices, and methods are disclosed for wireless communication of analyte data. In this regard, in embodiments, a mobile includes a transceiver configured to transmit and receive wireless signals. The mobile device includes circuitry operatively coupled to the transceiver. The mobile device also includes a non-transitory computer-readable medium operatively coupled to the circuitry and storing instructions that, when executed, cause the mobile device to perform a number of operations. One such operation is to obtain a derivative of a first signal received via a first link. Another such operation is to obtain a derivative of a second signal received via a second link; and. Yet another such operation is to generate a selection for connection to an analyte sensor system, based on a comparison of the derivative of the first signal and the derivative of the second signal.

Abstract: Systems, devices, and methods are disclosed for wireless communication of analyte data. In this regard, in embodiments, a mobile includes a transceiver configured to transmit and receive wireless signals. The mobile device includes circuitry operatively coupled to the transceiver. The mobile device also includes a non-transitory computer-readable medium operatively coupled to the circuitry and storing instructions that, when executed, cause the mobile device to perform a number of operations. One such operation is to obtain a derivative of a first signal received via a first link. Another such operation is to obtain a derivative of a second signal received via a second link; and. Yet another such operation is to generate a selection for connection to an analyte sensor system, based on a comparison of the derivative of the first signal and the derivative of the second signal.