Abstract: In some implementations, a data aggregator may receive an indication associated with a data record. The data aggregator may apply a model to the indication to generate a prediction regarding when new information associated with the data record will be available. Based on the prediction, the data aggregator may refrain from requesting new information and may schedule a pull for new information associated with the data record for a later time. Additionally, or alternatively, the data aggregator may receive an indication associated with a plurality of data pulls that are associated with a plurality of data records and may receive an indication of a rate limit associated with a host for the plurality of data records. The data aggregator may apply rules to generate a ranking of the plurality of data pulls and may schedule the plurality of data pulls based on the ranking and the rate limit.

Abstract: In some implementations, a data aggregator may receive an indication associated with a data record. The data aggregator may apply a model to the indication to generate a prediction regarding when new information associated with the data record will be available. Based on the prediction, the data aggregator may refrain from requesting new information and may schedule a pull for new information associated with the data record for a later time. Additionally, or alternatively, the data aggregator may receive an indication associated with a plurality of data pulls that are associated with a plurality of data records and may receive an indication of a rate limit associated with a host for the plurality of data records. The data aggregator may apply rules to generate a ranking of the plurality of data pulls and may schedule the plurality of data pulls based on the ranking and the rate limit.

Abstract: In some implementations, a data aggregator may receive an indication associated with a data record. The data aggregator may apply a model to the indication to generate a prediction regarding when new information associated with the data record will be available. Based on the prediction, the data aggregator may refrain from requesting new information and may schedule a pull for new information associated with the data record for a later time. Additionally, or alternatively, the data aggregator may receive an indication associated with a plurality of data pulls that are associated with a plurality of data records and may receive an indication of a rate limit associated with a host for the plurality of data records. The data aggregator may apply rules to generate a ranking of the plurality of data pulls and may schedule the plurality of data pulls based on the ranking and the rate limit.

Abstract: This invention relates to syndet-based compositions having pH of 4.5 to 5.5 wherein use of caprylic acid has been unexpectedly found to enhance bacterial kill.

Abstract: Methods for forecasting case counts for a future date in one or more geographic areas of persons infected by a disease is disclosed. The presence of the disease in a biological sample is testable by a polymerase chain reaction (PCR) test. A load of one or more pathogens associated with the disease correlates with a PCR cycle which indicates presence of the one or more pathogens, and is referred to as a threshold cycle (Ct). Data relevant to forecasting the case counts including Ct data and other data is received. The Ct data comprises Ct values from PCR tests of biological samples from persons within the one or more geographic areas. Arrays of feature data for processing by a trained machine learning model are generated, comprising Ct features and other features obtained from the data. A forecasted number of infected persons are generated by processing the arrays using machine learning.

Abstract: This invention relates to syndet-based compositions having pH of 4.5 to 5.5 wherein use of caprylic acid has been unexpectedly found to enhance bacterial kill.

Abstract: This invention relates to syndet-based compositions having pH of 4.5 to 5.5 wherein use of caprylic acid has been unexpectedly found to enhance bacterial kill.

Abstract: This invention relates to syndet-based compositions having pH of 4.5 to 5.5 wherein use of caprylic acid has been unexpectedly found to enhance bacterial kill.

Abstract: Methods of detecting nucleic acids, including methods of detecting nucleic acids in situ, are provided. The methods can detect even target nucleic acids that are partially degraded and/or masked by extensive crosslinking.

Abstract: Methods for making a differential diagnosis of hepatic neoplasms, e.g., tumors, and for identifying metastatic tumors of hepatic origin, based on detection of levels of albumin mRNA. The methods can also be used to select treatments or guide treatment decisions.

Abstract: The present application relates to methods for diagnosing and treating multiple myeloma (MM) and non-Hodgkin lymphoma (NHL), e.g., based on the detection of clonal IgK or IgL-expressing cells.

Abstract: Methods for diagnosing and treating IgG4-related disease (IgG4-RD), e.g., based on detecting levels of IgG4 mRNA, preferably using a branched DNA assay.