Abstract: Provided herein are drug implants comprising a therapeutically active agent for the treatment of disease in a subject. In some cases, the drug implant may comprise a polymer matrix and a therapeutically active agent disposed therein. Additionally, provided are methods for manufacturing the drug implants and methods of treating diseases with the implants. In some cases, the drug implant may comprise bicalutamide, e.g., for use in the treatment of prostate cancer.

Abstract: Provided herein are drug implants comprising a therapeutically active agent for the treatment of disease in a subject. In some cases, the drug implant may comprise a polymer matrix and a therapeutically active agent disposed therein. Additionally, provided are methods for manufacturing the drug implants and methods of treating diseases with the implants. In some cases, the drug implant may comprise bicalutamide, e.g., for use in the treatment of prostate cancer.

Abstract: A proactive networking system and method is disclosed. The network anticipates the user demands in advance and utilizes this predictive ability to reduce the peak to average ratio of the wireless traffic and yield significant savings in the required resources to guarantee certain Quality of Service (QoS) metrics. The system and method focuses on the existing cellular architecture and involves the design and analysis of learning algorithms, predictive resource allocation strategies, and incentive techniques to maximize the efficiency of proactive cellular networks. The system and method further involve proactive peer-to-peer (P2P) overlaying, which leverages the spatial and social structure of the network. Machine learning techniques are applied to find the optimal tradeoff between predictions that result in content being retrieved that the user ultimately never requests, and requests that are not anticipated in a timely manner.

Abstract: A proactive networking system and method is disclosed. The network anticipates the user demands in advance and utilizes this predictive ability to reduce the peak to average ratio of the wireless traffic and yield significant savings in the required resources to guarantee certain Quality of Service (QoS) metrics. The system and method focuses on the existing cellular architecture and involves the design and analysis of learning algorithms, predictive resource allocation strategies, and incentive techniques to maximize the efficiency of proactive cellular networks. The system and method further involve proactive peer-to-peer (P2P) overlaying, which leverages the spatial and social structure of the network. Machine learning techniques are applied to find the optimal tradeoff between predictions that result in content being retrieved that the user ultimately never requests, and requests that are not anticipated in a timely manner.

Abstract: Provided herein are drug implants comprising a therapeutically active agent for the treatment of disease in a subject. In some cases, the drug implant may comprise a polymer matrix and a therapeutically active agent disposed therein. Additionally provided are methods for manufacturing the drug implants and methods of treating diseases with the implants. In some cases, the drug implant may comprise bicalutamide, e.g., for use in the treatment of prostate cancer.

Abstract: Provided herein are drug implants comprising a therapeutically active agent for the treatment of disease in a subject. In some cases, the drug implant may comprise a polymer matrix and a therapeutically active agent disposed therein. Additionally provided are methods for manufacturing the drug implants and methods of treating diseases with the implants. In some cases, the drug implant may comprise bicalutamide, e.g., for use in the treatment of prostate cancer.

Abstract: Provided herein are drug implants comprising a therapeutically active agent for the treatment of disease in a subject. In some cases, the drug implant may comprise a polymer matrix and a therapeutically active agent disposed therein. Additionally provided are methods for manufacturing the drug implants and methods of treating diseases with the implants. In some cases, the drug implant may comprise bicalutamide, e.g., for use in the treatment of prostate cancer.

Abstract: Provided herein are drug implants comprising a therapeutically active agent for the treatment of disease in a subject. In some cases, the drug implant may comprise a polymer matrix and a therapeutically active agent disposed therein. Additionally provided are methods for manufacturing the drug implants and methods of treating diseases with the implants. In some cases, the drug implant may comprise bicalutamide, e.g., for use in the treatment of prostate cancer.

Abstract: Provided herein are drug implants comprising a therapeutically active agent for the treatment of disease in a subject. In some cases, the drug implant may comprise a polymer matrix and a therapeutically active agent disposed therein. Additionally provided are methods for manufacturing the drug implants and methods of treating diseases with the implants. In some cases, the drug implant may comprise bicalutamide, e.g., for use in the treatment of prostate cancer.

Abstract: Provided herein are drug implants comprising a therapeutically active agent for the treatment of disease in a subject. In some cases, the drug implant may comprise a polymer matrix and a therapeutically active agent disposed therein. Additionally provided are methods for manufacturing the drug implants and methods of treating diseases with the implants. In some cases, the drug implant may comprise bicalutamide, e.g., for use in the treatment of prostate cancer.

Abstract: A proactive networking system and method is disclosed. The network anticipates the user demands in advance and utilizes this predictive ability to reduce the peak to average ratio of the wireless traffic and yield significant savings in the required resources to guarantee certain Quality of Service (QoS) metrics. The system and method focuses on the existing cellular architecture and involves the design and analysis of learning algorithms, predictive resource allocation strategies, and incentive techniques to maximize the efficiency of proactive cellular networks. The system and method further involve proactive peer-to-peer (P2P) overlaying, which leverages the spatial and social structure of the network. Machine learning techniques are applied to find the optimal tradeoff between predictions that result in content being retrieved that the user ultimately never requests, and requests that are not anticipated in a timely manner.

Abstract: A proactive networking system and method is disclosed. The network anticipates the user demands in advance and utilizes this predictive ability to reduce the peak to average ratio of the wireless traffic and yield significant savings in the required resources to guarantee certain Quality of Service (QoS) metrics. The system and method focuses on the existing cellular architecture and involves the design and analysis of learning algorithms, predictive resource allocation strategies, and incentive techniques to maximize the efficiency of proactive cellular networks. The system and method further involve proactive peer-to-peer (P2P) overlaying, which leverages the spatial and social structure of the network. Machine learning techniques are applied to find the optimal tradeoff between predictions that result in content being retrieved that the user ultimately never requests, and requests that are not anticipated in a timely manner.

Abstract: A proactive networking system and method is disclosed. The network anticipates the user demands in advance and utilizes this predictive ability to reduce the peak to average ratio of the wireless traffic and yield significant savings in the required resources to guarantee certain Quality of Service (QoS) metrics. The system and method focuses on the existing cellular architecture and involves the design and analysis of learning algorithms, predictive resource allocation strategies, and incentive techniques to maximize the efficiency of proactive cellular networks. The system and method further involve proactive peer-to-peer (P2P) overlaying, which leverages the spatial and social structure of the network. Machine learning techniques are applied to find the optimal tradeoff between predictions that result in content being retrieved that the user ultimately never requests, and requests that are not anticipated in a timely manner.

Abstract: A proactive networking system and method is disclosed. The network anticipates the user demands in advance and utilizes this predictive ability to reduce the peak to average ratio of the wireless traffic and yield significant savings in the required resources to guarantee certain Quality of Service (QoS) metrics. The system and method focuses on the existing cellular architecture and involves the design and analysis of learning algorithms, predictive resource allocation strategies, and incentive techniques to maximize the efficiency of proactive cellular networks. The system and method further involve proactive peer-to-peer (P2P) overlaying, which leverages the spatial and social structure of the network. Machine learning techniques are applied to find the optimal tradeoff between predictions that result in content being retrieved that the user ultimately never requests, and requests that are not anticipated in a timely manner.

Abstract: A proactive networking system and method is disclosed. The network anticipates the user demands in advance and utilizes this predictive ability to reduce the peak to average ratio of the wireless traffic and yield significant savings in the required resources to guarantee certain Quality of Service (QoS) metrics. The system and method focuses on the existing cellular architecture and involves the design and analysis of learning algorithms, predictive resource allocation strategies, and incentive techniques to maximize the efficiency of proactive cellular networks. The system and method further involve proactive peer-to-peer (P2P) overlaying, which leverages the spatial and social structure of the network. Machine learning techniques are applied to find the optimal tradeoff between predictions that result in content being retrieved that the user ultimately never requests, and requests that are not anticipated in a timely manner.

Abstract: A proactive networking system and method is disclosed. The network anticipates the user demands in advance and utilizes this predictive ability to reduce the peak to average ratio of the wireless traffic and yield significant savings in the required resources to guarantee certain Quality of Service (QoS) metrics. The system and method focuses on the existing cellular architecture and involves the design and analysis of learning algorithms, predictive resource allocation strategies, and incentive techniques to maximize the efficiency of proactive cellular networks. The system and method further involve proactive peer-to-peer (P2P) overlaying, which leverages the spatial and social structure of the network. Machine learning techniques are applied to find the optimal tradeoff between predictions that result in content being retrieved that the user ultimately never requests, and requests that are not anticipated in a timely manner.

Abstract: A proactive networking system and method is disclosed. The network anticipates the user demands in advance and utilizes this predictive ability to reduce the peak to average ratio of the wireless traffic and yield significant savings in the required resources to guarantee certain Quality of Service (QoS) metrics. The system and method focuses on the existing cellular architecture and involves the design and analysis of learning algorithms, predictive resource allocation strategies, and incentive techniques to maximize the efficiency of proactive cellular networks. The system and method further involve proactive peer-to-peer (P2P) overlaying, which leverages the spatial and social structure of the network. Machine learning techniques are applied to find the optimal tradeoff between predictions that result in content being retrieved that the user ultimately never requests, and requests that are not anticipated in a timely manner.

Abstract: Methods of diagnosing and monitoring cancers and precancerous lesions associated with human papillomavirus (HPV), by detecting abnormal levels of lysine (K)-specific demethylase 6A (KDM6A), KDM6B, or trimethylated Histone H3 Lys27 (H3K27me3).

Abstract: An implantable medical device is provided for the treatment of a variety of disorders. The implantable medical device can be a neurostimulator having a stimulation lead and electrode(s) configured to be implanted on or near neural tissue in communication with the adrenal gland. Application of an electrical waveform to the neural tissue can cause the adrenal gland to release catecholamines to treat hypoglycemia. In other embodiments, chemical, magnetic, optical, or mechanical neuromodulation can be used.

Abstract: The invention features methods for treating and preventing a peripheral nerve sheath tumor in a mammal such as a human. The methods involve administering to the mammal a compound that modulates the biological activity of a gonatropic steroid receptor, such as the progesterone receptor in an amount sufficient to inhibit the growth of the peripheral nerve sheath tumor. The mammal may be administered with the compound alone or in combination with a second therapeutic regimen. Also disclosed are screening methods that make use of gonatropic steroid receptors for the identification of novel therapeutics for PNSTs.