A blood sample collector can be used to collect a blood sample from a subject. The blood sample collector can be placed in a receptacle of a spectrometer to measure spectral data from the blood sample while the blood sample separates. The container may comprise a window to allow light such as infrared light to pass through the container, with the blood sample at least partially separating within the container between spectral measurements, which can provide improved accuracy of the measurements and additional information regarding the sample. The container may comprise an elongate axis and the container configured for placement in the spectrometer receptacle with the elongate axis extending toward a vertical direction in order to improve gravimetric separation of the blood sample. The spectrometer can be configured to measure the blood sample at a plurality of heights along the sample as the sample separates.

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.

A reagent container is disclosed that is installed in an analyzer for use and stores a reagent supplied to the analyzer via an aspiration tube. The reagent container includes a container body. The container body includes a tubular member with an opening into which the aspiration tube is inserted from above, and a bag-shaped member joined to the tubular member and storing the reagent. The container body comprises a penetration prevention member that prevents a tip of the aspiration tube 90 inserted through the opening from penetrating the container body.

Disclosed are devices and methods for analyzing an analyte, such as white blood cells in liquid samples.

A method for in vitro simulation and evaluation of platelet adhesion in blood-contacting medical devices is disclosed, including the following steps: (1) using a glycerin aqueous solution with a mass percentage concentration of 40% in an extracorporeal circulation circuit to simulate a viscosity and hydrodynamic characteristics of blood, and adding fluorescent particles with a diameter of 3 μm to 5 μm to the solution to simulate platelets; (2) after the solution circulates in the circuit for a specified time period, removing flow passage components of a tested device, and observing the deposition of the fluorescent particles on a blood-contacting surface inside the device by naked eyes and photographs; and (3) using laser-induced fluorescence (LIF) technique to apply laser light on a device surface deposited with the fluorescent particles and in contact with blood, and using charge-coupled device (CCD) camera imaging to photograph the aggregation and adhesion of laser-induced fluorescent particles.

The present invention relates to a multisystem for simultaneously performing a biochemical examination and a blood test or an immunity test, the multisystem including a multi-disc in which a biochemical examination unit, a blood testing unit and an immunity test unit are divided and formed in a fan shape based on a rotation center. There is an effect that it is possible to perform all of a biochemical examination for measuring concentration values of biochemical components of serum to diagnose vital functions, a blood testing for separating blood samples to measure and test the number and deformation of red blood cells or white blood cells, and an immunity test for measuring an antigen-antibody reaction of serum to diagnose and test cancer or viruses in one device at the same time by using the multi-disc according to the present invention.

The types of cells that cannot be determined by use of a conventional scattergram are determined. The problem is solved by a cell analysis method for analyzing cells contained in a biological sample, by using a deep learning algorithm having a neural network structure, the cell analysis method including: causing the cells to flow in a flow path; obtaining a signal strength of a signal regarding each of the individual cells passing through the flow path, and inputting, into the deep learning algorithm, numerical data corresponding to the obtained signal strength regarding each of the individual cells; and on the basis of a result outputted from the deep learning algorithm, determining, for each cell, a type of the cell for which the signal strength has been obtained.

A sample analyzer with an optical detection device and a sample analysis method of the sample analyzer are disclosed. The optical detection device includes a fluid chamber, a light source and a light detector. The fluid chamber includes an illumination zone. An analyte flows through the illumination zone so as to form a sample stream. The light source illuminates the illumination zone to excite cell articles, reacted with a reagent, of the sample stream to emit a light signal. The light detector detects the fluorescent lights and transforms it into an electric signal. The light detector can include a silicon photomultiplier.

A method, system and storage medium for providing an alarm for indicating that an abnormality is present in a sample analyzer are provided. The method includes: mixing a first aliquot of a blood sample with a diluent agent to prepare a first test sample; mixing a second aliquot of the blood sample with a lytic reagent to prepare a second test sample; detecting electrical impedance signals of the first test sample; detecting at least two types of optical signals of the second test sample; acquiring first platelet detection data based on the electrical impedance signals; acquiring second platelet detection data based on the at least two types of optical signals; acquiring an evaluation result based on a difference between the first platelet detection data and the second platelet detection data; determining whether the evaluation result meets a preset condition to provide an alarm.

A sample analyzer includes a sample preparation device, an impedance testing device, an optical testing device, and a controller. The controller is configured to control the impedance testing device to test a first test sample to obtain a first platelet counting result for a test blood sample based on electronic information of the first test sample; control the optical testing device to test a second test sample to obtain a second platelet counting result for the test blood sample based only on optical information of the second test sample or based on both the electronic information of the first test sample and the optical information of the second test sample; determine whether the first platelet counting result is unreliable due to abnormality of the test blood sample; and output the first and/or the second platelet counting result according to the result of the determination.