FLOW CYTOMETER, CELL SORTER, OPTICAL INFORMATION GENERATION METHOD, AND PROGRAM

    公开(公告)号:US20230266229A1

    公开(公告)日:2023-08-24

    申请号:US18118670

    申请日:2023-03-07

    Applicant: ThinkCyte K.K.

    CPC classification number: G01N15/1459 G01N15/1484 G01N15/1436 G01N2015/1006

    Abstract: A flow cytometer includes: a light source; a microfluidic device; a photodetector; an information generation device which generates optical information indicating a morphology of an observation target on the basis of optical signal intensity; and a spatial light modulation unit which is installed on an optical path between the light source and the photodetector and structures any one of illumination light irradiated from the light source toward the flow path and signal light from the observation target. In the flow path provided with the microfluidic device, a plurality of optical signal detection positions are arranged linearly at equal intervals in a predetermined direction of the flow path by structuring the illumination light or the signal light and a plurality of trigger signal detection positions for detecting a trigger signal by which the information generation device starts the generation of the optical information are arranged to be separated by the same predetermined distance in a length direction of the flow path while respectively corresponding to the plurality of optical signal detection positions.

    FLOW CELL OF FLOW CYTOMETER AND CLEANING METHOD OF FLOW CELL OF FLOW CYTOMETER

    公开(公告)号:US20230039952A1

    公开(公告)日:2023-02-09

    申请号:US17794187

    申请日:2021-01-21

    Applicant: ThinkCyte K.K.

    Abstract: A flow cell of the flow cytometer of the present invention includes: a sample flow path through which a sample fluid containing a sample flows; and a sample fluid supply portion which communicates with an upstream end of the sample flow path in the sample fluid flow direction and supplies the sample fluid to the sample flow path, wherein the sample fluid supply portion includes a plurality of sample opening portions which supply a sample fluid to the sample flow path, a cleaning liquid supply opening portion to which a second tube is connectable and which supplies a cleaning liquid for cleaning the sample fluid supply portion, and a cleaning liquid discharge opening portion to which a first tube is connectable and which discharges the cleaning liquid from the sample fluid supply portion.

    FLOW CYTOMETER, DISCRIMINATION METHOD, AND PROGRAM

    公开(公告)号:US20250060301A1

    公开(公告)日:2025-02-20

    申请号:US18915034

    申请日:2024-10-14

    Applicant: ThinkCyte K.K.

    Abstract: A flow cytometer includes: a flow channel allowing a measurement object not labeled with a fluorescent dye to flow along with a fluid; a light source emitting illumination light; an illumination optical system irradiating the measurement object flowing in the flow channel with the illumination light emitted from the light source as a spotlight which is illumination light condensed in at least one of a width direction and a depth direction of the flow channel at an irradiation position in the flow channel; a light detector detecting fluorescence emitted from a specific molecule of the measurement object in response to irradiation with the spotlight via the illumination optical system; a detection optical system allowing the fluorescence to propagate to the light detector; and a discrimination unit configured to discriminate whether the measurement object is a target measurement object based on information of the fluorescence detected by the light detector.

    SYSTEMS AND METHODS OF MACHINE LEARNING-BASED SAMPLE CLASSIFIERS FOR PHYSICAL SAMPLES

    公开(公告)号:US20240362462A1

    公开(公告)日:2024-10-31

    申请号:US18648216

    申请日:2024-04-26

    Applicant: ThinkCyte K.K.

    CPC classification number: G06N3/0455 G06N3/09

    Abstract: Systems and methods are provided to implement classification of objects, based on sensor data regarding the objects, without labels assigned to the sensor data. A system can include one or more processors. The one or more processors can retrieve sensor data regarding an object. The one or more processors can apply the sensor data as input to a classification model to cause the classification model to determine a classification of the object. The classification model can be configured based on training data that includes a plurality of clusters generated by dimensionality reduction of example data regarding example objects. At least one cluster of the plurality of clusters can be associated with the classification. The one or more processors can output the classification of the object.

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