Intelligent Virus Imaging Inc

Intelligent Virus Inc.

Ida-Maria Sintorn

Gustaf Kylberg

Rickard Nordstrom Nordstrom

Lars Haag

Göran Stemme

Niclas Roxhed

Mohammed Homman

Martin Ryner

Josefina Nilsson

Janosch Hauser

The microfluidic device has a first reservoir that preferably includes a first liquid. The first liquid is being held by a capillary stop valve in the first reservoir. A second reservoir is in fluid communication with the first reservoir. The second reservoir has a second liquid and a sample support disposed therein. The second reservoir has an inlet opening defined therein. A draining unit is adjacent to the second reservoir. The draining unit is in fluid communication with the second reservoir. The draining unit has a first absorption member disposed therein.

Autonomous microfluidic device for sample preparation

The method is for preparing a sample in a microfluidic device. A microfluidic device is provided that has a first reservoir in fluid communication with a second reservoir in fluid communication with and adjacent to a draining unit that has a first absorbing member disposed therein. The first reservoir contains a first liquid that is held in the first reservoir by a capillary stop valve connecting the first and second reservoirs. The second reservoir has a sample support disposed therein. A second liquid, containing substances, is added to the second reservoir. The second liquid contacts the first liquid and the first absorbing member. The first absorbing member absorbs the second liquid and the first liquid. The substances adhere to the sample support.

The method is for quantification of purity of sub-visible particle samples. A sample to be analyzed is place in an electron microscope to obtain an electron microscopy image of the sample. The sample contains objects. The objects that have sizes being different from a size range of primary particles and sizes being within the size range of primary particles are enhanced. The objects are detected as being primary particles or debris. The detected primary particles are excluded from the objects so that the objects contain debris but no primary particles. A first total area (T1) of the detected debris is measured. A second total area (T2) of the detected primary particles is measured.

Method for quantification of purity of sub-visible particle samples

The method is for quantification of sub-visible particles. A filter membrane is provided that has a plurality of pores defined therethrough. The pores are sealed with a sealant such as glycine or poly-vinyl alcohol (PVA). A sample droplet, containing liquid and sub-visible particles, is applied onto the filter membrane. The liquid dissolves the sealant in pores disposed directly below the sample droplet. The liquid flows through the pores in which the sealant has been dissolved and the sub-visible particles remain on top of the filter membrane. The particles are enumerated in an electron microscope.

High precision quantification of sub-visible particles

The method is for quantification of sub-visible particles. A filter membrane is provided that has a plurality of pores defined therethrough. The filter membrane is in operational engagement with a vacuum chamber. The pores are sealed with a sealant. A sample droplet, containing a liquid and sub-visible particles, is applied onto the filter membrane. The liquid dissolves the sealant in pores disposed directly below the sample droplet. The liquid flows through the pores in which the sealant has been dissolved and the sub-visible particles remain on top of the filter membrane. The particles are enumerated in an electron microscope.

The method is for quantification of sub-visible particles. A filter membrane is provided that has a plurality of pores defined therethrough. The filter membrane is in operational engagement with a vacuum chamber. The pores are sealed with a sealant. A sample droplet, containing a liquid and sub-visible particles, is applied onto the filter membrane. The liquid dissolves the sealant in pores disposed directly below the sample droplet. The liquid flows through the pores in which the sealant has been dissolved and the sub-visible particles remain on top of the filter membrane. The particles are enumerated in an electron microscopy.

The method is for automatic astigmatism correction of a lens system. A first image of a first frequency spectrum in a microscope is provided. The first image of a view is not in focus. The first image is then imaged. A first roundness measure of a distribution and directions of intensities in the first image is determined. The lens is changed to a second stigmator setting to provide a second image of a second frequency spectrum. The second image of the view is not in focus. The second image is the same view as the first image of the view at the first stigmator setting. A second roundness measure of a distribution and directions of intensities in the second image is determined. The first roundness measure is compared with the second roundness measure. The image with the roundness measure indicating the roundest distribution is selected.

Method for automatic correction of astigmatism

The method is for automatic astigmatism correction of a lens system. A first image is provided that is not in focus at a first stigmator setting of a set of lenses. A calculating device calculates a corresponding first Fourier spectrum image. A distribution and direction of pixels of the Fourier spectrum image are determined by calculating a first vector and a second vector. The first vector is compared with the second vector. The lens system is changed from a first stigmator setting to a second stigmator setting to provide a second image. A corresponding Fourier spectrum image is calculated. The distribution and direction of pixels of the second Fourier spectrum image is determined by calculating a third vector and a fourth vector. The third vector is compared to the fourth vector. The image that has the lowest vector ratio is selected.

A cell is provided that contains a plurality of virus particles. A first image of a first virus particle and a second image of a second virus particle are taken by electron microscopy technology. The first virus particle is characterized as being in a first maturity stage and the second virus particle as being in a second maturity stage. The first image and the second image are transformed to first and second gray scale profiles, respectively, based on pixel data. The first and second gray scale profiles are then saved as first and second templates, respectively. A third virus particle in a third image is identified. The third image is transformed into a third gray scale profile. The third gray scale is compared to the first and second template to determine a maturity stage of the third virus particle.

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Sollentuna, Sweden

Ida-Maria Sintorn