Aspects of the present disclosure include methods for characterizing particles of a sample in a flow stream. Methods according to certain embodiments include generating frequency-encoded fluorescence data from a particle of a sample in a flow stream; and calculating phase-corrected spatial data of the particle by performing a transform of the frequency-encoded fluorescence data with a phase correction component. In certain embodiments, methods include generating an image of the particle in the flow stream based on the phase-corrected spatial data. Systems having a processor with memory operably coupled to the processor having instructions stored thereon, which when executed by the processor, cause the processor to calculate phase-corrected spatial data from frequency-encoded fluorescence data of a particle a flow stream are also described. Integrated circuit devices (e.g., field programmable gate arrays) having programming for practicing the subject methods are also provided.

A method for measuring concentrations of blood cell components is provided. The method comprises: obtaining a blood sample from a subject, the blood sample comprising at least one of red blood cells (RBCs), white blood cells (WBCs), and platelets (PLTs); mixing the blood sample with a non-lysing aqueous solution to form a sample mixture comprising a predetermined tonicity; passing the sample mixture through a flow cell; emitting light towards the flow cell; measuring at least one of an amount of light absorbed by the RBCs to obtain an RBC absorption value, an amount of light scattered by WBCs to obtain a WBC scatter value, and an amount of light scattered by PLTs to obtain a PLT scatter value; and determining a concentration of at least one of the RBCs, WBCs, and PLTs present in the sample mixture.

The present invention relates generally to an apparatus for identifying biological particles. More particularly, the present invention relates to a small apparatus for identifying biological particles, wherein in a single apparatus having a simple structure, a cleaning solution is suctioned to separate the biological particles from a filter and a sample solution is discharged, the discharged sample solution is injected into a plurality of ticket modules, and the biological particles are identified by image analysis for the ticket modules, thereby enabling miniaturization of the apparatus.

Aspects of the present disclosure include methods and systems for automated analysis of clinical fluid samples, such as urine, blood, or cerebral spinal fluid, where the number of fluid samples in increased or optimized without negatively impacting the accuracy of the analysis of a given fluid sample.

The present invention relates generally to the field of plastic microparticles. In particular, the present invention relates to the detection of plastic microparticles in a water-based sample. An embodiment of the present invention relates to a process for detecting and characterizing plastic microparticles in a water-based sample comprising the analysis of the sample by spectral flow cytometry. In accordance with the present invention, the process described herein may comprise the processing of the recorded flow cytometry data by a machine learning algorithm that can distinguish and categorize each particle based on its unique spectrum to characterize, for example, the plastic microparticles.

An imaging flow cytometer includes: a laser unit that emits first and second laser light to first and second spots; a first and second imaging sections that image the first and second spots; first and second detection devices that detect a particle that passes through the first and second spots; a first particle detection section that issues an imaging timing instruction signal to the first and second imaging sections; an image storage section that receives an image imaged by the first and second imaging sections; and a sorting determination section that determines whether the particle is an objective particle. The first and second imaging sections clip an image of the particle based on the imaging timing instruction signal.

The disclosed apparatus, systems and methods relate to technology that provides a method for the assessment of the polymerization of a sample, e.g., whole blood or blood plasma coagulation, by a non-contact acoustic tweezing device via the application of a sweeping frequency to the levitating sample and the corresponding assessment of extracted sample parameters.

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.

Provided herein are techniques for label free cell sorting. The systems and methods provided herein may use machine learning based image classification techniques to identify cells of interest within a sample of cells. The cells of interest may then be separated from the sample using mechanical, pneumatic, piezoelectric, and/or electronic devices.

A method for analyzing microorganisms arranged in a sample is provided, the sample including a viability marker to modify an optical property of the microorganisms in different ways depending on whether they are dead or alive, the method including illumination of the sample and acquisition of an image of the latter by an image sensor, the image sensor then being exposed to an exposure light wave; determining positions of different microorganisms from the acquired image; applying a propagation operator to calculate at least one characteristic value of the exposure light wave at each radial position and at a plurality of distances from the detection plane representing a change in the characteristic value between the image sensor and the sample; and identifying living microorganisms according to each profile.