Patent classifications
G01N2015/1014
Multiple flow channel particle analysis system
A microfluidic multiple channel particle analysis system which allows particles from a plurality of particle sources to be independently simultaneously entrained in a corresponding plurality of fluid streams for analysis and sorting into particle subpopulations based upon one or more particle characteristics.
Identification device and identification method
The identification apparatus includes a quantitative phase image acquisition unit, a feature quantity extraction unit, a learning unit, a storage unit, and an identification unit. The feature quantity extraction unit extracts a feature quantity of a quantitative phase image of a cell. The learning unit performs machine learning for a quantitative phase image of a known cell of which a type is known based on the feature quantity extracted by the extraction unit. The storage unit stores a result of the machine learning by the learning unit. The identification unit determines, based on the feature quantity extracted by the extraction unit for the quantitative phase image of an unknown cell of which a type is unknown, the type of the unknown cell using the learning result stored by the storage unit.
CALIBRATION OBJECT FOR CALIBRATING AN IMAGING SYSTEM
A calibration object for calibrating an imaging system includes a discrete entity with a calibration pattern. The discrete entity is made of at least one transparent polymeric compound.
Synthetic human cell mimic particle for cytometric or coulter device
Synthetic human cell mimic hydrogel particles and their use in cytometric or coulter device applications are described. The synthetic human cell mimic hydrogel particles described herein are selectively tunable to have at least one optical, volumetric, or capacitance property that is substantially similar to a corresponding optical, volumetric, or capacitance property of the human cell mimic hydrogel particle's natural biological cell counterpart.
Image analysis and measurement of biological samples
Methods, devices, systems, and apparatuses are provided for the image analysis of measurement of biological samples.
Direct detection of single molecules on microparticles
The disclosure provides methods of analyzing an analyte of interest in a biological sample using fluorescent agents and macroconjugates which comprise a core containing a cross-linked polymer or protein, tags, specific binding members or fragments thereof, and optionally carrier proteins. Also provided are methods of analyzing two or more analytes of interest in a biological sample in a single assay using microparticles and detection conjugates comprising different fluorophore labels, acquiring transmitted light and fluorescent images of the microparticles, and using a customized image analysis process to analyze the acquired images.
POLYDISPERSED PARTICLE CHALLENGE SAMPLE VOLUME CALIBRATION OF OPTICAL PARTICLE COUNTERS
A method of calibrating an optical particle counter may include performing first and second calibration procedures. The first calibration procedure may include performing sensitivity calibration and/or channel size calibration of the optical particle counter under calibration using a monodispersed particle standard. The second calibration procedure may include sample volume calibration. The sample volume calibration may include: flowing a polydispersed particle calibration sample dispersed in a fluid through the optical particle counter under calibration to produce a first signal output; flowing the polydispersed particle calibration sample dispersed in the fluid through a reference optical particle counter to produce a reference signal output; comparing the first signal output with the reference signal output; and adjusting, in response to the comparing, an effective sample volume parameter stored in a computer readable memory of the optical particle counter under calibration.
Method for determining abnormality in particle analyzer and particle analyzer
Disclosed is a method for determining abnormality in a particle analyzer. The method includes: staining first control particles but not staining second control particles which emit fluorescence; irradiating with light the first control particles and the second control particles flowing in a flow cell, and detecting fluorescence from the first control particles and the second control particles; obtaining a first management value indicating a detection result of the fluorescence emitted from the first control particles and a second management value indicating a detection result of the fluorescence emitted from the second control particles; and determining abnormality in the staining step, based on a value calculated from the first management value and the second management value or a ratio between the first management value and the second management value.
Nanoparticles for self referencing calibration
Systems and methods for high-throughput processing of assay plates include a calibration nanoparticle to facilitate automated focusing of the imaging system. An assay plate includes a base layer, a transparent layer in contact with the base layer, and at least one calibration nanoparticle having a pre-defined size immobilized on the assay plate surface. The assay plate surface can be functionalized to selectively bind to biological targets. The assay plate can be used in an imaging system for high-throughput autofocus and biological target detection.
SYSTEMS AND METHODS FOR DIAGNOSING A FLUIDICS SYSTEM AND DETERMINING DATA PROCESSING SETTINGS FOR A FLOW CYTOMETER
The present set of embodiments relates to systems and methods for diagnosing a fluidics system and determining data processing settings for a flow cytometer. Systems and methods for diagnosing a fluidics system require accurate measurement and interpretation of fluctuations within the fluid delivery system. Systems and methods for determining data processing settings require an accurate measurement of peak times among various channels and being able to adjust time delay settings wherein peak time is the measurement of time elapsed from the beginning of the data collection time window to the highest peak in the window.