Abstract: A cell sorting device is disclosed, wherein the device includes a sorting magnet and at least one particle manipulation device, wherein the particle manipulation device is formed on a surface of a fabrication substrate. The device may include at least one fluid channel, wherein the sorting magnet and the particle manipulation device are in fluid communication with one another through at least one fluid channel. A method of sorting cells from a first cell suspension is also disclosed, The method may include a) magnetic labeling of first target cells and removal of the non-target cells by applying magnetic fields to obtain a second cell suspension; b) fluorescence-activated labeling of second target cells present in the second cell suspension and separating the fluorescence-activated second target cells from the not labeled cells to obtain a third cell suspension.

Abstract: A microfabricated droplet dispensing structure is described, which may include a MEMS microfluidic fluidic valve, configured to open and close a microfluidic channel. The opening and closing of the valve may separate a target biological particle containing genomic material, and a bead from a sample stream, and direct these two particle into a single droplet formed at the edge of the substrate. The droplet may then be encased in a sheath flow of an immiscible fluid, and provided to a downstream workflow.

Abstract: A convolutional neural network (CNN) is applied to identifying tumors in a histological image. The CNN has one channel assigned to each of a plurality of tissue classes that are to be identified, there being at least one class for each of non-tumorous and tumorous tissue types. Multi-stage convolution is performed on image patches extracted from the histological image followed by multi-stage transpose convolution to recover a layer matched in size to the input image patch. The output image patch thus has a one-to-one pixel-to-pixel correspondence with the input image patch such that each pixel in the output image patch has assigned to it one of the multiple available classes. The output image patches are then assembled into a probability map that can be co-rendered with the histological image either alongside it or over it as an overlay. The probability map can then be stored linked to the histological image.

Abstract: Glue bottle anti-clog caps are provided. The anti-clog cap has a body with a mounting section for attaching the body to a glue bottle. The body of the anti-clog cap has a dispensing section that includes a central lumen extending from the second mounting end. The body of the anti-clog cap also has a tip section with a support rib protruding from an outlet of the dispensing section. The tip has a tip plug protruding from the support rib. The anti-clog cap has a nozzle that mates to the body and a tip orifice aligned with the tip plug of the body. The tip section is configured to allow the free flow of glue through the cap. The nozzle can rotate between an open and closed position. In the closed position the tip plug can extend into the tip orifice thereby preventing the flow of glue.

Abstract: A microfabricated droplet dispensing structure is described, which may include a MEMS microfluidic fluidic valve, configured to open and close a microfluidic channel. The opening and closing of the valve may separate a target particle and a bead from a sample stream, and direct these two particle into a single droplet formed at the edge of the substrate. The droplet may then be encased in a sheath flow of an immiscible fluid.

Abstract: A convolutional neural network (CNN) is applied to identifying tumors in a histological image. The CNN has one channel assigned to each of a plurality of tissue classes that are to be identified, there being at least one class for each of non-tumorous and tumorous tissue types. Multi-stage convolution is performed on image patches extracted from the histological image followed by multi-stage transpose convolution to recover a layer matched in size to the input image patch. The output image patch thus has a one-to-one pixel-to-pixel correspondence with the input image patch such that each pixel in the output image patch has assigned to it one of the multiple available classes. The output image patches are then assembled into a probability map that can be co-rendered with the histological image either alongside it or over it as an overlay. The probability map can then be stored linked to the histological image.

Abstract: A particle manipulation system uses a MEMS-based, microfabricated particle manipulation device which has a sample inlet channel, output channels, and a movable member formed on a substrate. The device may be used to separate a target particle from non-target material in a sample stream. In order to improve the sorter speed, accuracy or yield, the particle manipulation system may also include a microfluidic structure which focuses the target particles in a particular portion of the sample inlet channel. The particle manipulation device may have two separate sort output channels, wherein the sort channel used depends on the characteristics of the sort pulse delivered to the micromechanical particle manipulation device.

Abstract: Described here is a microfabricated particle sorting device that uses a transient pulse of fluidic pressure to deflect the target particle. The transient pulse may be generated by a microfabricated (MEMS) actuator, which pushes a volume of fluid into a channel, or sucks a volume of fluid from the channel. The transient pressure pulse may divert a target particle into a sort channel.

Abstract: Described here is a microfabricated particle sorting device that uses a transient pulse of fluidic pressure to deflect the target particle. The transient pulse may be generated by a microfabricated (MEMS) actuator, which pushes a volume of fluid into a channel, or sucks a volume of fluid from the channel. The transient pressure pulse may divert a target particle into a sort channel.

Abstract: A particle manipulation system uses a MEMS-based, microfabricated particle manipulation device which has a sample inlet channel, output channels, and a movable member formed on a substrate. The device may be used to separate a target particle from non-target material in a sample stream. In order to improve the sorter speed, accuracy or yield, the particle manipulation system may also include a microfluidic structure which focuses the target particles in a particular portion of the sample inlet channel. This focusing element may include cavities of variable cross section along the channel length. In addition, a filtering element may also be included upstream of the focusing element.

Abstract: Background tasks are managed through background task settings that allow or prevent the execution of agents associated with mobile device applications in the background of a mobile computing device. Background task management can extend the battery life of a mobile device and can be done by a user, the mobile device or a combination thereof. Agents scheduled for execution by a mobile device are executed according to the background task settings associated with the application. Background task settings can be controlled via background task control panels. Background task settings can be set on a system-wide, application or background task basis. Disabled background tasks can be enabled when the application is next launched. A user can be invited to navigate to the background task control panels when various events occur such as the battery life dropping below a threshold or the current power consumption exceeding a threshold.

Abstract: Background tasks are managed through background task settings that allow or prevent the execution of agents associated with mobile device applications in the background of a mobile computing device. Background task management can extend the battery life of a mobile device and can be done by a user, the mobile device or a combination thereof. Agents scheduled for execution by a mobile device are executed according to the background task settings associated with the application. Background task settings can be controlled via background task control panels. Background task settings can be set on a system-wide, application or background task basis. Disabled background tasks can be enabled when the application is next launched. A user can be invited to navigate to the background task control panels when various events occur such as the battery life dropping below a threshold or the current power consumption exceeding a threshold.

Abstract: Background tasks are managed through background task settings that allow or prevent the execution of agents associated with mobile device applications in the background of a mobile computing device. Background task management can extend the battery life of a mobile device and can be done by a user, the mobile device or a combination thereof. Agents scheduled for execution by a mobile device are executed according to the background task settings associated with the application. Background task settings can be controlled via background task control panels. Background task settings can be set on a system-wide, application or background task basis. Disabled background tasks can be enabled when the application is next launched. A user can be invited to navigate to the background task control panels when various events occur such as the battery life dropping below a threshold or the current power consumption exceeding a threshold.

Abstract: A method is provided for displaying a client-side multi-component image. A plurality of image component channels derived from captured images of a sample are stored in a server, the plurality of image component channels being stored in the form of a plurality of image data records. A client then requests one or more of the plurality of image data records and the server transmits to the client the one or more of the plurality of image data records requested. At the client, the client-side multi-component image is composited from the image data records transmitted the composited client-side multi-component image is displayed.