Abstract: The present invention provides novel amino chromen-2-one compounds that are inhibitors of mitochondrial RNA polymerase for treating various diseases such as cancer and others associated with metabolic disorders and mitochondrial dysfunction.

Abstract: Disclosed are compounds according to Formula (1) which inhibit LONP1, and pharmaceutical compositions comprising compounds of the disclosure. Compounds and pharmaceutical compositions of the disclosure may be useful for the treatment of diseases and disorders associated with LONP1, including oncologic diseases and disorders, such as cancer, and diseases and disorders related to mitochondrial dysfunction, such as neurodegenerative disorders, metabolic disorders, and diseases associated with the aging process. The disclosure also relates to methods of using such compounds and compositions for the treatment of such diseases and disorders.

Abstract: The present disclosure is directed to a method for screening a signal peptide for efficient expression and secretion of a heterologous polypeptide in mammalian cells, the method comprising the steps of: providing a pool of viral expression vectors encoding a polypeptide of interest with various candidate signal peptides, wherein each viral expression vector of said pool comprises at least a polynucleotide encoding a fusion protein, said polynucleotide comprising: i) a promoter, ii) a sequence encoding a signal peptide, iii) a sequence encoding the polypeptide of interest, iv) optionally a sequence encoding an epitope tag, and v) a sequence encoding a C-terminal signal peptide for glycosylphosphatidylinositol, GPI, attachment or a sequence encoding a transmembrane domain; transforming host cells with said pool of viral vectors so that each host cell is preferably transformed on average by only one viral vector from said pool; expressing said fusion protein in said host cells in order to produce fusion proteins

Abstract: Disclosed are compounds according to Formula (1) and Formula (2) which inhibit LONP1, and pharmaceutical compositions comprising compounds of the disclosure. Compounds and pharmaceutical compositions of the disclosure may be useful for the treatment of diseases and disorders associated with LONP1, including oncologic diseases and disorders, such as cancer, and diseases and disorders related to mitochondrial dysfunction, such as neurodegenerative disorders, metabolic disorders, and diseases associated with the aging process. The disclosure also relates to methods of using such compounds and compositions for the treatment of such diseases and disorders.

Abstract: Enhanced capabilities within a telephone network are made accessible to a telecommunications device. The telecommunications device is used to dial a sequence. A network server receives and identifies the sequence invokes an advanced network function. A advanced network function server in communication with the network server provides instructions as to how the network server is to provide the advanced network function. The network server processes the call in accordance with the received instructions to provide the particular advanced network function.

Abstract: Disclosed are compounds according to Formula (1) which inhibit LONP1, and pharmaceutical compositions comprising compounds of the disclosure. Compounds and pharmaceutical compositions of the disclosure may be useful for the treatment of diseases and disorders associated with LONP1, including oncologic diseases and disorders, such as cancer, and diseases and disorders related to mitochondrial dysfunction, such as neurodegenerative disorders, metabolic disorders, and diseases associated with the aging process. The disclosure also relates to methods of using such compounds and compositions for the treatment of such diseases and disorders.

Abstract: A novel distributed method for machine learning is described, where the algorithm operates on a plurality of data silos, such that the privacy of the data in each silo is maintained. In some embodiments, the attributes of the data and the features themselves are kept private within the data silos. The method includes a distributed learning algorithm whereby a plurality of data spaces are co-populated with artificial, evenly distributed data, and then the data spaces are carved into smaller portions whereupon the number of real and artificial data points are compared. Through an iterative process, clusters having less than evenly distributed real data are discarded. A plurality of final quality control measurements are used to merge clusters that are too similar to be meaningful. These distributed quality control measures are then combined from each of the data silos to derive an overall quality control metric.

Abstract: A novel distributed method for machine learning is described, where the algorithm operates on a plurality of data silos, such that the privacy of the data in each silo is maintained. In some embodiments, the attributes of the data and the features themselves are kept private within the data silos. The method includes a distributed learning algorithm whereby a plurality of data spaces are co-populated with artificial, evenly distributed data, and then the data spaces are carved into smaller portions whereupon the number of real and artificial data points are compared. Through an iterative process, clusters having less than evenly distributed real data are discarded. A plurality of final quality control measurements are used to merge clusters that are too similar to be meaningful. These distributed quality control measures are then combined from each of the data silos to derive an overall quality control metric.

Abstract: A novel distributed method for machine learning is described, where the algorithm operates on a plurality of data silos, such that the privacy of the data in each silo is maintained. In some embodiments, the attributes of the data and the features themselves are kept private within the data silos. The method includes a distributed learning algorithm whereby a plurality of data spaces are co-populated with artificial, evenly distributed data, and then the data spaces are carved into smaller portions whereupon the number of real and artificial data points are compared. Through an iterative process, clusters having less than evenly distributed real data are discarded. A plurality of final quality control measurements are used to merge clusters that are too similar to be meaningful. These distributed quality control measures are then combined from each of the data silos to derive an overall quality control metric.

Abstract: A novel distributed method for machine learning is described, where the algorithm operates on a plurality of data silos, such that the privacy of the data in each silo is maintained. In some embodiments, the attributes of the data and the features themselves are kept private within the data silos. The method includes a distributed learning algorithm whereby a plurality of data spaces are co-populated with artificial, evenly distributed data, and then the data spaces are carved into smaller portions whereupon the number of real and artificial data points are compared. Through an iterative process, clusters having less than evenly distributed real data are discarded. A plurality of final quality control measurements are used to merge clusters that are too similar to be meaningful. These distributed quality control measures are then combined from each of the data silos to derive an overall quality control metric.

Abstract: Described herein are avian follistatin products, and methods for producing such products, in which such products are effective for a variety of conditions, including increasing muscle mass. Avian follistatin products described herein are packaged as dietary supplements or nutritional supplements are useful in muscle regeneration.

Abstract: A novel distributed method for machine learning is described, where the algorithm operates on a plurality of data silos, such that the privacy of the data in each silo is maintained. In some embodiments, the attributes of the data and the features themselves are kept private within the data silos. The method includes a distributed learning algorithm whereby a plurality of data spaces are co-populated with artificial, evenly distributed data, and then the data spaces are carved into smaller portions whereupon the number of real and artificial data points are compared. Through an iterative process, clusters having less than evenly distributed real data are discarded. A plurality of final quality control measurements are used to merge clusters that are too similar to be meaningful. These distributed quality control measures are then combined from each of the data silos to derive an overall quality control metric.

Abstract: Devices and methods are provided for collecting and handling difficult sample types.

Abstract: Devices and methods are provided for collecting and handling difficult sample types.

Abstract: A technology is described for monitoring interaction events at services and determining service management actions associated with the services. An example method may include receiving metadata describing interaction events at services executing in a computing service environment and using the metadata to generate a routing map that provides routing details for the interaction events at the services. The routing map may be analyzed to identify interaction characteristics associated with the interaction events at the services and the analysis of the routing map may be used in determining a service management action associated with the services based in part on the interaction characteristics associated with the interaction events.

Abstract: A packaging system for film including: a controller; and a seal jaw controlled by the controller, wherein the seal jaw includes: a first sealing bar; a second sealing bar; a servo motor controlling movement of at least one of the first and the second sealing bars between an open position and a closed position, where the sealing bars are in contact; and a pneumatic cylinder, connected with at least one of the first and second sealing bars, and controlling a pressure between the sealing bars when in the closed position. A method of creating a seal in packaging film, the method including: moving, via a servo motor, a first sealing bar and a second sealing bar from an open position to a closed position; and upon reaching the closed position, clamping, via a pneumatic cylinder, the sealing bars to create a seal in the packaging film.

Abstract: A technology is provided for generating a customized application program interface (API) in a service provider environment. A model is created of computing resources and data hosted by a service provider environment. An API is generated based on the model for the computing resources and the data, wherein the API is configured to enable the client to access the computing resources and data. Calls are received from the client at an API gateway hosting the API to access the data and the computing resources hosted by the service provider environment. A response to the calls is sent wherein the response is generated by the computing resources using the data accessible to the API in the service provider environment.

Abstract: A technology is described for embedding hypermedia resources in data interchange format documents. An example method may include receiving an API (Application Program Interface) request for a hypermedia resource at an API server. The API request may be associated with an API request pattern, where the API request pattern includes API requests for hypermedia resources. A data interchange format document may be generated to include the hypermedia resource requested and at least one of the hypermedia resources associated with the API request pattern may be embedded in the data interchange format document. The data interchange format document may be provided in response to the API request.

Abstract: A technology is described for embedding hypermedia resources in data interchange format documents. An example method may include receiving an instruction to request a first hypermedia resource from an API (Application Program Interface) server. A second hypermedia resource related to the first hypermedia resource may be identified. A probability that the second hypermedia resource may be requested may be calculated and a determination based in part on the probability that the second hypermedia resource will be requested may be made. Thereafter, an API request for the first hypermedia resource that includes hint data that identifies the second hypermedia resource may be generated.