Non-parametric transforms such as t-distributed stochastic neighbor embedding (tSNE) are used to analyze multi-parametric data such as data derived from flow cytometry or other particle analysis systems and methods. These transforms may be included for dimensionality reduction and identification of subpopulations (e.g., gating). By nature, non-parametric transforms cannot transform new observations without training a new transformation based on the entire dataset including the new observations. The features described parameterize non-parametric transforms using a neural network thereby allowing a small training dataset to be transformed using non-parametric techniques. The training dataset may then be used to generate an accurate parametric model for assessing additional events in a manner consistent with the initial events.

Aspects of the present disclosure include methods for determining a parameter of a photodetector (e.g., a photodetector in a particle analyzer). Methods according to certain embodiments include detecting light from a light source with a photodetector for a first predetermined time interval, detecting a step signal with the photodetector, the step signal indicating a change in a parameter of the light source or a parameter of the photodetector, detecting light from the light source for a second predetermined time interval, integrating data signals over the first predetermined time interval and the second predetermined time interval and determining one or more parameters of the photodetector based on the integrated data signals. Systems (e.g., particle analyzers) having a light source and a photodetector for practicing the subject methods are also described. Non-transitory computer readable storage medium having instructions stored thereon for determining a parameter of a photodetector according to the subject methods is also provided.

Provided herein are kits comprising (a) erythrosin B (EB); (b) adsorbent; and (c) instructions for use. Also provided are methods of determining the percentage of dead bacteria in a bacterial cell population. The methods comprise (a) obtaining a bacterial cell population; (b) contacting the bacterial cell population with an erythrosin B (EB) solution; (c) contacting the bacterial cell population and EB with an adsorbent to remove excess EB; (d) transferring the non-adsorbed bacterial cell population and EB solution; and (e) determining the percentage of dead bacteria in the bacterial cell population.

Aspects of the present disclosure include methods for detecting events in a flow cytometer. Also provided are methods of detecting cells in a flow cytometer. Other aspects of the present disclosure include methods for determining a level of contamination in a flow cell. Computer-readable media and systems, e.g., for practicing the methods summarized above, are also provided.

Various embodiments described herein relate to apparatuses and methods for detecting fluid particles and their characteristics. In various embodiments, a device for detecting fluid particles and their characteristics may comprise a fluid composition sensor configured to receive a volume of fluid. The fluid composition sensor has a collection media housing configured to receive a portion of a collection media, a pump for moving a volume of fluid over the collection media housing, an imaging device configured to capture an image of particles on the collection media, and a particle matter mass concentration calculation circuitry configured to calculate a total particle matter mass. The particle matter mass concentration calculation circuitry is connected with the imaging device and the pump. The particle matter mass concentration calculation circuitry is configured to adjust the volume of fluid over the collection media housing.

The invention relates to a method of determining whether a host has an infection. The method comprises obtaining measured values comprising a number of leukocytes and a number of a first type of leukocytes in a blood sample from the host, and comparing the measured values with one or more stored threshold value(s) to determine whether the host has said infection.

Aspects of the present disclosure include methods for processing cytometer data, such as for group-wise analysis of the cytometer data (e.g., flow cytometry data in FCS format, mass cytometry data, genomic cytometry data). Methods according to certain embodiments include generating a compound population of events that include data accessors from cytometry data, such as where the compound population of cytometer data is from two or more different samples retained as separate raw data files (e.g., are not concatenated to form a single combined data file). Systems having an input module for receiving cytometer data and processor with memory having instructions for practicing the subject methods are also described. Non-transitory computer readable storage medium is also provided.

A modular optical particle counter sensor and apparatus are described that consolidates counting functionality on a single main counter board and has expandable functionality through connections to plug-in system boards. The modular optical particle sensor may be directly connected to a manifold with an integrated Venturi for better controlling the flow rate of the air stream passing through the apparatus for sampling.

An information processing apparatus including a dimension compression section that generates dimension-compressed data for input data on the basis of a learning model generated by a neural network in which same data acquired from a biologically derived substance is applied to an input layer and an output layer.

Disclosed are systems, devices and methods for imaging and image-based sorting of particles in a flow system, including cells in a flow cytometer. In some aspects, a system includes a particle flow device to flow particles through a channel, an imaging system to obtain image data of a particle during flow through the channel, a processing unit to determine a property associated with the particle and to produce a control command for sorting the particle based on sorting criteria associated with particle properties, and an actuator to direct the particle into one of a plurality of output paths of the particle flow device in real-time.