In the present technology, an object of the present disclosure is to provide a new technique for addressing the clogging in a flow channel through which a biological sample flows. The present disclosure provides a biological sample analysis device including an information processing unit configured to perform abnormality determination processing of detecting an abnormality in a flow channel through which a biological sample flows on the basis of clogging detection data, in which the clogging detection data is data related to the number of detected particles per unit time. The abnormality determination processing may include sorting area clogging determination processing for detecting clogging in a sorting area where the particles are sorted, supply area clogging determination processing for detecting clogging in a supply area for supplying the biological sample to the sorting area where the particles are sorted, or both the sorting area clogging determination processing and the supply area clogging determination processing.

Disclosed herein are a particle sorting device capable of simply detecting bubbles, foreign substances, or the like in droplets, a method for analyzing particles, a program, and a particle sorting system. The particle sorting device includes a judgment unit, and the judgment unit judges whether or not captured image information including captured droplet image information about a brightness of an image of particle-containing droplets captured after discharge from an orifice has changed with respect to previously-set reference image information including reference droplet image information about a brightness of an image of droplets captured after discharge from the orifice.

A flow cytometer apparatus and methods for detecting and clearing a clog therein are disclosed. An example method for detecting a clog may include (i) detecting, via a fault detection system of a flow cytometer, a first plurality of events associated with a first aliquot from a first sample well, (ii) determining a count of the first plurality of events associated with the first aliquot, (iii) determining whether the count of the first plurality of events is below a minimum count tolerance and (iv) (a) if the count of the first plurality of events is below the minimum count tolerance, then determining that the flow cytometer has a clog, (b) if the count of the first plurality of events is equal to or above the minimum count tolerance, then detecting a second plurality of events associated with a second aliquot from a second sample well.

A flow cytometer apparatus and methods for detecting and clearing a clog therein are disclosed. An example method for detecting a clog may include (i) detecting, via a fault detection system of a flow cytometer, a first plurality of events associated with a first aliquot from a first sample well, (ii) determining a count of the first plurality of events associated with the first aliquot, (iii) determining whether the count of the first plurality of events is below a minimum count tolerance and (iv) (a) if the count of the first plurality of events is below the minimum count tolerance, then determining that the flow cytometer has a clog, (b) if the count of the first plurality of events is equal to or above the minimum count tolerance, then detecting a second plurality of events associated with a second aliquot from a second sample well.

The present disclosure discloses a data acquisition and analysis method based on diabetes data analysis and processing equipment, and relates to the field of diabetes data analysis and prediction. The equipment includes a computer, a placement rack and a flow cytometer. The mitochondrial membrane potential data in the neutrophil is performed independent evaluation and analysis. If the proportion of cells with increased mitochondrial membrane potential are in the neutrophil is greater than 70%, the person is at the risk of diabetes, otherwise the risk is lower, so that the subsequent development of diabetes in a person with normal blood glucose can be predicted, and the diabetes can be prevented in advance.

A system includes a flow cell and a fluidics system under pressure causing sheath and sample biological fluids to flow. The fluidics system includes a gas bubble remover to remove and eliminate gas bubbles in the sheath fluid. The flow cell receives sheath fluid from the fluidics system, wherein the sample biological fluid flows with cells or particles through the flow cell to be surrounded by the sheath fluid. A deflection chamber under the flow cell receives drops of the sample biological fluid and sheath fluid out of the flow cell to selectively deflect one or more of the drops along one or more deflection paths. A droplet deposition unit system in communication with the deflection chamber receives the selectively deflected drops in the stream of the sample biological fluid with the one or more biological cells or particles into one or more containers.