The present invention provides devices and systems for use at the point of care. The methods devices of the invention are directed toward automatic detection of analytes in a bodily fluid. The components of the device are modular to allow for flexibility and robustness of use with the disclosed methods for a variety of medical applications.

In one embodiment, a method is provided comprising analyte testing on one or more types of samples.

The present disclosure provides a HTP microbial genomic engineering platform that is computationally driven and integrates molecular biology, automation, and advanced machine learning protocols. This integrative platform utilizes a suite of HTP molecular tool sets to create HTP genetic design libraries, which are derived from, inter alga, scientific insight and iterative pattern recognition. The HTP genomic engineering platform described herein is microbial strain host agnostic and therefore can be implemented across taxa. Furthermore, the disclosed platform can be implemented to modulate or improve any microbial host parameter of interest.

The present invention relates to an automatic specimen feeding system and a control method therefor, the automatic specimen feeding system comprising: a main frame installed adjacent to a carbon measuring apparatus, having a space with an open upper portion, and being provided with an input hole for inputting a specimen into the carbon measuring apparatus; a specimen seating unit which reciprocates horizontally in a direction perpendicular to the carbon measuring apparatus while moving up and down with respect to the main frame, and on which a plurality of specimens can be seated; a specimen lift unit which is installed under the specimen seating unit and can lift one of the plurality of specimens seated on the specimen seating unit; and a specimen input unit which is installed lengthways in the direction towards the carbon measuring apparatus to grip specimens lifted by the specimen lift unit and to input the specimens into the carbon measuring apparatus. Therefore, a plurality of specimens can be automatically input into the carbon measuring apparatus and used specimens can be discarded without using manpower, and thus user convenience can be improved. In addition, processes of inputting specimens can be minimized to noticeably reduce the time taken to automatically measure carbon by using specimens.

The present disclosure provides a HTP microbial genomic engineering platform that is computationally driven and integrates molecular biology, automation, and advanced machine learning protocols. This integrative platform utilizes a suite of HTP molecular tool sets to create HTP genetic design libraries, which are derived from, inter alia, scientific insight and iterative pattern recognition. The HTP genomic engineering platform described herein is microbial strain host agnostic and therefore can be implemented across taxa. Furthermore, the disclosed platform can be implemented to modulate or improve any microbial host parameter of interest.

The present disclosure provides a HTP microbial genomic engineering platform that is computationally driven and integrates molecular biology, automation, and advanced machine learning protocols. This integrative platform utilizes a suite of HTP molecular tool sets to create HTP genetic design libraries, which are derived from, inter alia, scientific insight and iterative pattern recognition. The HTP genomic engineering platform described herein is microbial strain host agnostic and therefore can be implemented across taxa. Furthermore, the disclosed platform can be implemented to modulate or improve any microbial host parameter of interest.

Provided are an automatic analyzer and an optical measurement method for correcting a variation in the multiplication factor of a photoelectric element with high accuracy. The automatic analyzer comprises: a photoelectric element which generates electrons by light and outputs a current signal; a voltage application unit which applies a voltage to the photoelectric element; and a processing unit which corrects a variation in the multiplication factor of the photoelectric element, wherein the photoelectric element outputs a pulse signal as the current signal, and the processing unit corrects the variation in the multiplication factor on the basis of the pulse area of the pulse signal.

The present disclosure provides a HTP microbial genomic engineering platform that is computationally driven and integrates molecular biology, automation, and advanced machine learning protocols. This integrative platform utilizes a suite of HTP molecular tool sets to create HTP genetic design libraries, which are derived from, inter alia, scientific insight and iterative pattern recognition. The HTP genomic engineering platform described herein is microbial strain host agnostic and therefore can be implemented across taxa. Furthermore, the disclosed platform can be implemented to modulate or improve any microbial host parameter of interest.

A laboratory sample distribution system is presented. The laboratory sample distribution system comprises an optical inspection device adapted to optically inspect items that need to be optically inspected, at least one mirror device, a driver adapted to move the items to be optically inspected and to move the at least one mirror device, and a control device configured to move an item to be optically inspected relative to the optical inspection device by controlling the driver such that a field of view of the optical inspection device is extended.

The present disclosure provides a HTP microbial genomic engineering platform that is computationally driven and integrates molecular biology, automation, and advanced machine learning protocols. This integrative platform utilizes a suite of HTP molecular tool sets to create HTP genetic design libraries, which are derived from, inter alia, scientific insight and iterative pattern recognition. The HTP genomic engineering platform described herein is microbial strain host agnostic and therefore can be implemented across taxa. Furthermore, the disclosed platform can be implemented to modulate or improve any microbial host parameter of interest.