A microscope system is provided with a microscope that acquires images at least at a first magnification and a second magnification higher than the first magnification, and a processor. The processor is configured to specify a type of a container in which a specimen is placed, and when starting observation of the specimen placed in the container at the second magnification, the processor is configured to specify an observation start position by performing object detection according to the type of container on a first image that includes the container acquired by the microscope at the first magnification, and control a relative position of the microscope with respect to the specimen such that the observation start position is contained in a field of view at the second magnification of the microscope.

Methods, devices, and systems for improving the quality of electrospray ionization mass spectrometer (ESI-MS) data are described, as are methods, devices, and systems for achieving improved correlation between chemical separation data and mass spectrometry data.

Automatic substance preparation and evaluation systems and methods are provided for preparing and evaluating a fluidic substance, such as e.g. a sample with bodily fluid, in a container and/or in a dispense tip. The systems and methods can detect volumes, evaluate integrities, and check particle concentrations in the container and/or the dispense tip.

Automatic substance preparation and evaluation systems and methods are provided for preparing and evaluating a fluidic substance, such as e.g. a sample with bodily fluid, in a container and/or in a dispense tip. The systems and methods can detect volumes, evaluate integrities, and check particle concentrations in the container and/or the dispense tip.

A system for identifying microbial agents such as virus particles in a sample. The system includes at least one processing unit for identifying in an electron micrograph obtained from the sample a darker region and identifying virus particles within the darker region. The system can optionally include an electron microscope, a sample collector and sample treatment chamber.

The proposed model is a Variational Autoencoder having a learnable prior that is parametrized with a Tensor Train (VAE-TTLP). The VAE-TTLP can be used to generate new objects, such as molecules, that have specific properties and that can have specific biological activity (when a molecule). The VAE-TTLP can be trained in a way with the Tensor Train so that the provided data may omit one or more properties of the object, and still result in an object with a desired property.

The proposed model is a Variational Autoencoder having a learnable prior that is parametrized with a Tensor Train (VAE-TTLP). The VAE-TTLP can be used to generate new objects, such as molecules, that have specific properties and that can have specific biological activity (when a molecule). The VAE-TTLP can be trained in a way with the Tensor Train so that the provided data may omit one or more properties of the object, and still result in an object with a desired property.

This disclosure describes single-use test cartridges, cell analyzer apparatus, and methods for automatically performing microscopic cell analysis tasks, such as counting and analyzing blood cells in biological samples. A small measured quantity of a biological sample, such as whole blood, is placed in a mixing bowl on the disposable test cartridge after being inserted into the cell analyzer. The analayzer also deposits a known amount of diluent/stain in the mixing bowl and mixes it with the blood. The analyzer takes a measured amount of the mixture and dispenses in a sample cup on the cartridge in fluid communication with an imaging chamber. The geometry of the imaging chamber is chosen to maintain the uniformity of the mixture, and to prevent cells from crowding or clumping as it is transferred into the imaging chamber by the analyzer. Images of all of the cellular components within the imaging chamber are counted and analyzed to obtain a complete blood count.

This disclosure describes single-use test cartridges, cell analyzer apparatus, and methods for automatically performing microscopic cell analysis tasks, such as counting and analyzing blood cells in biological samples. A small measured quantity of a biological sample, such as whole blood, is placed in a mixing bowl on the disposable test cartridge after being inserted into the cell analyzer. The analayzer also deposits a known amount of diluent/stain in the mixing bowl and mixes it with the blood. The analyzer takes a measured amount of the mixture and dispenses in a sample cup on the cartridge in fluid communication with an imaging chamber. The geometry of the imaging chamber is chosen to maintain the uniformity of the mixture, and to prevent cells from crowding or clumping as it is transferred into the imaging chamber by the analyzer. Images of all of the cellular components within the imaging chamber are counted and analyzed to obtain a complete blood count.

A system and method for analyzing bodily fluid include a sample holder holding a bodily fluid sample, an image capture device generating an image of the bodily fluid sample comprising a plurality of fields of view. An image processor is programmed to determine a biofilm in the bodily fluid sample from the image, determine a biofilm area or volume within each of the plurality of fields of view to form a plurality of biofilm areas, determine a total biofilm area or total biofilm volume by adding the plurality of biofilm areas, determine a first value corresponding to a comparison of the total biofilm area or the total biofilm volume and a total volume of the bodily fluid sample, and classify the first value into a classification. An analyzer, using the classification, displays an indicator on a display for indicating the classification of the biofilm within the bodily fluid sample.