CPC Class C12Q

A method for at least one of characterizing, diagnosing, and treating a condition associated with microbiome-derived functional features in at least a subject, the method comprising: receiving an aggregate set of biological samples from a population of subjects; generating at least one of a microbiome composition dataset and a microbiome functional diversity dataset for the population of subjects; generating a characterization of the condition based upon features extracted from at least one of the microbiome composition dataset and the microbiome functional diversity dataset; based upon the characterization, generating a therapy model configured to correct the condition; and at an output device associated with the subject, promoting a therapy to the subject based upon the characterization and the therapy model.

A method for at least one of characterizing, diagnosing, and treating a condition associated with microbiome-derived functional features in at least a subject, the method comprising: receiving an aggregate set of biological samples from a population of subjects; generating at least one of a microbiome composition dataset and a microbiome functional diversity dataset for the population of subjects; generating a characterization of the condition based upon features extracted from at least one of the microbiome composition dataset and the microbiome functional diversity dataset; based upon the characterization, generating a therapy model configured to correct the condition; and at an output device associated with the subject, promoting a therapy to the subject based upon the characterization and the therapy model.

Embodiments of the present disclosure relate to analyte determining methods and devices (e.g., electrochemical analyte monitoring systems) that have a sensing surface that includes two or more sensing elements disposed laterally to each other, where the sensing surface is on a working electrode of in vivo and/or in vitro analyte sensors, e.g., continuous and/or automatic in vivo monitoring using analyte sensors and/or test strips. Also provided are systems and methods of using the, for example electrochemical, analyte sensors in analyte monitoring.

Embodiments of the invention provide analyte sensors having optimized elements and/or configurations of elements as well as methods for making and using such sensors. Typical embodiments of the invention include glucose sensors used in the management of diabetes.

This disclosure relates to a nanoporous composition including a number of clusters of nanoparticles dispersed in a liquid, a nanoporous layer formed of the nanoporous composition, a glucose-oxidation electrode including the nanoporous layer, and a glucose-sensing device and system including the glucose-oxidation electrode. This disclosure also relates to a method of making the nanoporous composition, the nanoporous layer, the glucose-oxidation electrode and the glucose-sensing device and system. Further, this disclosure also relates to devices, systems and methods for continuous glucose monitoring (CGM) and blood glucose monitoring (BGM).

Systems and methods for processing sensor data and self-calibration are provided. In some embodiments, systems and methods are provided which are capable of calibrating a continuous analyte sensor based on an initial sensitivity, and then continuously performing self-calibration without using, or with reduced use of, reference measurements. In certain embodiments, a sensitivity of the analyte sensor is determined by applying an estimative algorithm that is a function of certain parameters. Also described herein are systems and methods for determining a property of an analyte sensor using a stimulus signal. The sensor property can be used to compensate sensor data for sensitivity drift, or determine another property associated with the sensor, such as temperature, sensor membrane damage, moisture ingress in sensor electronics, and scaling factors.